Systems and methods for electroencephalogram monitoring

ABSTRACT

Provided herein are systems, kits, and methods for monitoring brain activity. In some implementations, a system includes a plurality of wearable sensors having a housing with an extended, rounded shape are removably attached to the scalp of a patient and monitor electroencephalogram (EEG) signals. Approaches for instructing a user to position and active that wearable sensors are disclosed. Approaches for facilitating collection, synchronization, and processing of EEG signals are disclosed. Approaches for handing off control of the wearable sensors between portable computing devices are disclosed.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority to U.S. Provisional Patent ApplicationNo. 63/380,132 filed on Oct. 19, 2022, which is incorporated byreference in its entirety.

STATEMENT REGARDING FEDERALLY SPONSORED R&D

This invention was made with Government support under Grant Nos.4U44NS121562-03 and 5SB1NS100235-06, awarded by the Department of Healthand Human Services. The Government has certain rights in the invention.

TECHNICAL FIELD

This application relates to systems and methods for monitoring brainactivity using one or more wireless electroencephalogram sensors.

BACKGROUND

An electroencephalogram (“EEG”) is a diagnostic tool that measures andrecords the electrical activity of a person's brain in order to evaluatecerebral functions. Multiple electrodes are attached to a person's headand connected to a machine by wires. The machine amplifies the signalsand records the electrical activity of a person's brain. The electricalactivity is produced by the summation of neural activity across aplurality of neurons. These neurons generate small electric voltagefields. The aggregate of these electric voltage fields create anelectrical reading which electrodes on the person's head are able todetect and record. An EEG is a superposition of multiple simplersignals. In a normal adult, the amplitude of an EEG signal typicallyranges from 1 micro-Volt to 100 micro-Volts, and the EEG signal isapproximately 10 to 20 milli-Volts when measured with subduralelectrodes. The monitoring of the amplitude and temporal dynamics of theelectrical signals provides information about the underlying neuralactivity and medical conditions of the person.

There are thousands of hospitals across the United States. Many of thesehospitals are community or rural hospitals. These community or ruralhospitals conventionally are part of a hospital system or network. Anexample of one such network includes several community hospitals withone major tertiary hospital. A community or rural hospital outside ofany large hospital network would typically contract with a largetertiary hospital for emergent and intensive-care solutions outside ofthe areas of expertise of the community or rural hospital.

EEG monitoring is conventionally only available in the large tertiaryhospitals that support a neurology department with an EEG service. Manyhospitals do not offer EEG monitoring. These hospitals make arrangementswith larger tertiary hospitals or their partners when such monitoring isrequired or desirable for patients. This conventionally takes the formof a referral of the patient to the tertiary hospital for expert ofspecialist services. Often this includes travel or transport of thepatient to the tertiary hospital for services. This creates manyproblems particularly for patients in rural areas. As a result, it isdesirable to provide improvements in EEG monitoring systems and methods.

SUMMARY

An EEG can be performed to diagnose epilepsy, verify problems with lossof consciousness or dementia, verify brain activity for a person in acoma, study sleep disorders, monitor brain activity during surgery, andmonitor additional physical problems.

Disclosed herein are systems and methods for monitoring brain activityusing one or more wireless EEG sensors configured to be removably placedin one or more locations on a scalp of a patient. One or more computingdevices can communicate with the EEG sensors and facilitate setting upthe EEG sensors, receiving, and processing EEG data collected by the EEGsensors. Advantageously, accurate EEG measurements can be obtained andprocessed to determine one or more physiological conditions of apatient, such as seizures, epilepsy, or the like. In addition, disclosedsystems and method allow non-experts to set-up EEG monitoring so that amuch larger patient population can benefit from the monitoring.

BRIEF DESCRIPTION OF THE DRAWINGS

In the following description, various implementations will be described.For purposes of explanation, specific configurations and details are setforth in order to provide a thorough understanding of theimplementations. However, it will also be apparent to one skilled in theart that the implementations may be practiced without the specificdetails. Furthermore, well-known features may be omitted or simplifiedin order not to obscure the implementation being described.

FIG. 1A is a perspective top view and bottom view illustration of an EEGrecording wearable sensor.

FIGS. 1B to 1D are various views of an EEG recording wearable sensor.

FIG. 2A illustrates an example attachment.

FIG. 2B illustrates an example attachment placed onto the wearablesensor, aligned over the electrodes.

FIG. 2C illustrates an example sensor placed onto a patient's scalp.

FIGS. 3A to 3C are exploded views of attachments.

FIG. 4 is a front perspective view illustration of a charger.

FIG. 5 illustrates a kit or system for monitoring brain activity.

FIG. 6 is an illustration of an EEG monitoring system.

FIG. 7A illustrates a flow diagram of a process for set-up of a session.

FIGS. 7B to 7K illustrate example screens associated with sensoractivation and sensor placement displayed on a portable computingdevice.

FIG. 7L is a flow diagram of a process for sensor set-up andprovisioning.

FIG. 8 is an illustration of a sensor control transfer environment.

FIGS. 9A to 9E illustrates examples screens associated with datarecording and sensor management displayed on a portable computingdevice.

FIG. 10A illustrates a method of synchronizing sensor data for aplurality of independent wireless EEG sensors.

FIG. 10B illustrates an alternative method of synchronizing sensor datafor a plurality of independent wireless EEG sensors.

DETAILED DESCRIPTION Overview

Certain EEG monitoring systems can include complicated multi-componentmedical device systems, which require technical skill for set-up andcoordination. When such systems are used outside of a large or researchhospital with special expertise, set-up and coordination can bedifficult and prone to user error. EEG monitoring systems which usemultiple sensor components also require time synchronization acrossindividual devices in order to combine sensor data. When the devices arenot wired together, achieving time synchronization of sensor acrossmultiple sensor devices can be difficult to achieve. EEG monitoringsystems may also be used for long-term use, either at home or in ahospital of any given size or specialty including, for example, smallgeneral hospitals in rural areas. Long-term EEG recording requires ahigh level of complexity in set up and coordination but needs to beseamless and simple for day-to-day use.

EEG monitoring systems and methods have been described in U.S. Pat. No.11,020,035 and in U.S. Patent Publication No. 2021/0307672, each ofwhich are incorporated by reference in their entirety.

Described herein are improved systems, kits, and methods for EEGmonitoring.

Wearable Sensor and EEG Monitoring Kit

FIG. 1A is a perspective top view and bottom view illustration of an EEGrecording wearable sensor 101, which can be used as a seizure monitoringtool. As shown in FIG. 1A, the wearable sensor 101 is self-contained ina housing 102. The housing 102 may be formed of a plastic, polymer,composite, or the like that is water-resistant, waterproof, or the like.

The housing 102 can contain all of the electronics for recording EEGfrom at least two electrodes 104, 105. The electrodes 104, 105 are onthe bottom, or scalp facing, side shown on the right side of FIG. 1A.Electrodes 104, 105 may be formed of any suitable material. For example,electrodes 104, 105 may comprise gold, silver, silver-silver chloride,carbon, combinations of the foregoing, or the like. One of theelectrodes 104, 105 can be a reference electrode and the other can be ameasurement (or measuring) electrode. As noted above, the entirewearable sensor 101 may be self-contained in a watertight housing 102.The wearable sensor 101 can be designed to be a self-contained EEGmachine that is one-time limited use per user and disposable. Thewearable sensor 101 can include more than two electrodes. In some cases,the wearable sensor 101 includes three electrodes. In someimplementations, the wearable sensor 101 includes four electrodes.Additional electrodes (such as a third and/or fourth electrode) may beformed of any suitable material, for example gold, silver, silver-silverchloride, carbon, combinations of the foregoing, or the like.

The wearable sensor 101 has two electrodes 104, 105 and can be usedalone or in combination with other wearable sensors 101 (such as, threeother wearable sensors 101) as a discrete tool to monitor seizures (andin some cases count seizures). It may be desirable, but not necessary,that the user has had a previous diagnosis of a seizure disorder using atraditional wired EEG based on the 10-20 montage. This diagnosisprovides clinical guidance as to the most optimal location to place thewearable sensor 101 for recording electrographic seizure activity in anindividual user. In some cases, the electrode 104, 105 spacing uses abipolar derivation to form a single channel of EEG data.

FIG. 1B is a perspective top view illustration of an EEG recordingwearable sensor 101 with a housing 102 that has an extended, roundedshape. Such shape can be referred to as a jellybean shape, and mayfacilitate accurate placement on a patient in a correct orientation aswell as promote patient comfort and prolonged wear.

In some cases, the EEG recording wearable sensor 101 is shaped to fitbehind the ear. The EEG recording wearable sensor 101 can be shaped tofit along the hairline. The EEG recording wearable sensor 101 can beshaped to fit along a scalp. For example, as shown in FIG. 1B, the EEGrecording wearable sensor 101 has an extended rounded shape which isconfigured to fit around or complement a hairline of a user, such thatthe extended, rounded shape of the housing 102 facilitates unobtrusivewear of the sensor on the scalp of the user while facilitatingcollection of the EEG signals. In some implementations, the housing 102includes a narrow portion configured to curve around the hairline of auser. FIG. 1C provides a cross-sectional view, and FIG. 1D provides aperspective view of the EEG recording wearable sensor 101 of FIG. 1B.FIGS. 1C-1D illustrate that the housing 102 includes a narrow portion110. The side of the housing 102 with the narrow portion 110 can bepositioned closer to the patient's ear (see FIG. 2C), which canfacilitate unobtrusive wear and collection of the EEG signals. Thenarrow portion 110 can be thinner than other parts of the housing 102.The housing 102 can become thicker (or widen) from the end that includesthe narrow portion 110 to the opposite end 111. Such varying thicknessof the housing 102 can facilitate unobtrusive wear. Thickness of thehousing 102 in the widest portion can be about 10.0 mm, 9.5 mm, 9.0 mm,8.5 mm, 8.0 mm, 7.5 mm, 7.0 mm, 6.5 mm, 6.0 mm, 5.5 mm, 5.0 mm, 4.5 mm,4.0 mm, or within a range constructed from any of the aforementionedvalues.

In some implementations, the EEG recording wearable sensor 101 is shapedto mimic the look of hearing aids. The EEG recording wearable sensor 101can include an antenna. The external design (jellybean shape) of the EEGrecording wearable sensor 101 can influence the internal shape,requiring unique design and tuning of the antenna.

In some cases, the EEG recording wearable sensor 101 includes a powersource supported by the housing and configured to provide power to theelectronic circuitry. In some cases, the EEG recording wearable sensor101 includes a rechargeable battery. The EEG recording wearable sensor101 can includes electrode. The EEG recording wearable sensor 101 caninclude at least two electrodes positioned on an exterior surface of thehousing and configured to detect EEG signals indicative of a brainactivity of the user when the housing is positioned on a scalp of theuser. The electrodes may be disposed within the housing 102 of the EEGrecording wearable sensor 101. Unlike traditional wired EEG systemsemploying the 10-20 montage, the EEG recording wearable sensor 101 canallow a much smaller spacing between the measurement and referenceelectrodes, which may not only make the housing 102 more compact, butalso improve signal quality. The distance between the electrodes can beconfigured to allow for less noisy EEG signal capture, thus improvingsignal quality. The distance between the electrodes can be reduced,particularly when compared to traditional wired EEG systems employingthe 10-20 montage. The distance between electrodes can be no more thanabout 25 mm center to center, no more than about 20 mm center to center,no more than about 18 mm center to center, no more than about 15 mmcenter to center, no more than about 10 mm center to center, or within arange constructed from any of the aforementioned values. The housing 102can be configured so that the electrodes are disposed at a distanceconfigured to allow better EEG signal capture.

The EEG recording wearable sensor 101 includes an electronic circuitrythat may be supported by the housing 102. The electronic circuitry canbe configured to process the EEG signals detected by the at least twoelectrodes. In some implementations, the electronic circuitry isconfigured to wirelessly communicate processed EEG signal to a remotecomputing device. The remote computing device can be a portablecomputing device as described herein.

An extended, rounded shape for an EEG recording wearable sensor 101 mayallow an EEG recording wearable sensor 101 to provide: (a) properelectrode pair spacing to allow EEG signal capture; (b) an enclosedhousing 102 large enough to contain a full electronics package,including an antenna and a battery that supports frequent communication(such as, Bluetooth or Bluetooth low energy (BLE)); and/or (c) a housing102 design that complements the curvature around a scalp and/or ahairline and/or behind ears.

In some cases, the surface area of the housing 102 is about 8.5 cm², 8.0cm², 7.5 cm², 7.0 cm², 6.5 cm², 6.0 cm², 5.5 cm², 5.0 cm², 4.5 cm², orwithin a range constructed from any of the aforementioned values. Thesurface area of the jellybean shaped housing 102 illustrated in FIG. 1Bcan be about 20 cm², 19.5 cm², 19.0 cm², 18.5 cm², 18.0 cm², 17.5 cm²,17.0 cm², 16.5 cm², 16.0 cm², 15.5 cm², 15.0 cm², 14.5 cm², 14.0 cm²,13.5 cm², 13.0 cm², 12.5 cm², 12.0 cm², 11.5 cm², 11.0 cm², 10.5 cm²,10.0 cm², 9.5 cm², 9.0 cm², 8.5 cm², 8.0 cm², 7.5 cm², 7.0 cm², 6.5 cm²,6.0 cm², 5.5 cm², 5.0 cm², 4.5 cm² or less, or within a rangeconstructed from any of the aforementioned values. The volume of thejellybean shaped housing 102 illustrated in FIG. 1B can be about 8.0cm³, 7.5 cm³, 7.0 cm³, 6.5 cm³, 6.0 cm³, 5.0 cm³, 4.5 cm³, 4.0 cm³, 3.5cm³, 3.0 cm³, 2.5 cm³, 2.0 cm³ or less, or within a range constructedfrom any of the aforementioned values. The wearable sensor 101 can beplaced anywhere on the scalp of a patient to record EEG (such as, behindthe ear).

The wearable sensor 101 may be packaged such that removal from thepackage activates the circuitry. Implementations of the wearable sensor101 can be placed anywhere on the scalp as placing a conventional wiredEEG electrode. The wearable sensor 101 can self-adhere to the scalpeither through a conductive adhesive, an adhesive with a conductive,and/or through mechanical means such as intradermal fixation with amemory-shape metal, or the like.

Once attached to the scalp (for instance, with an attachment asdescribed below), some implementations enable the wearable sensor 101 toperform as seizure detection device (alone or in combination with one ormore other wearable sensors 101, such as three other wearable sensors101). The wearable sensor 101 can record EEG continuously, uninterruptedfor up to seven days. In some implementations, each EEG recordingwearable sensor 101 is configured to detect EEG signals independent ofthe other sensors. Following a recording session, the wearable sensor101 may be placed in the mail and returned to a service that reads theEEG to identify epileptiform activity according to ACNS guidelines. Insome cases, data may be retrieved from the wearable sensor 101 via anI/O data retrieval port (not shown) and uploaded or otherwise sent to aservice for reading the EEG data. The I/O data retrieval port mayoperate with any suitable I/O protocol, such as USB protocol, Bluetoothprotocol, or the like. Epileptiform activity such as seizures andinterictal spikes may be identified in a report along with EEG recordingattributes and made available to physicians through a user's electronicmedical records, or the like.

The wearable sensor 101 may employ capacitive coupling as a means tospot-check signal quality. A handheld, or other device, can be broughtnear the wearable sensor 101 to capacitively couple with the device as ameans to interrogate the EEG or impedance signal in real time.

The wearable sensor 101 may be used to alert to seizures in real time,or near real time. The wearable sensor 101 may continuously transmit toa base station (not shown) that runs seizure detection algorithm(s) inreal-time. The base station may sound an alarm if a seizure is detectedeither at the base station itself, or through communication to otherdevices (not shown) capable of providing a visual and/or audio and/ortactile alarm. The base station may also keep a record of EEG for laterreview by an epileptologist. These EEG may also be archived inelectronic medical records, or otherwise stored.

The wearable sensor 101 could be used to record ultra-low frequencyevents from the scalp such as cortical spreading depressions. Amplifiercircuitry (not shown) may be appropriate for recording DC signals.Alternatively, the amplifier circuitry may be appropriate for recordingboth DC and AC signals. The wearable sensor 101 may be used after asuspected stroke event as a means to monitor for the presence or absenceof cortical spreading depressions and/or seizures or other epileptiformactivity. The wearable sensor 101 may be placed on the scalp of apatient by any type of health care provider such as an emergency medicaltechnician, medical doctor, nurse, or the like.

In some implementations, the wearable sensor 101 may employ capacitivecoupling to monitor for cortical spreading depressions in real time. Thespreading depressions could be analyzed over time and displayed as avisualization of the EEG. The wearable sensor 101 may store these EEG(e.g., in storage) for later retrieval. These EEG could also be archivedin electronic medical records, or the like.

FIG. 2A depicts an attachment 200 being peeled off a backing 201 toreveal an adhesive side. The attachment 200 can be referred to as asticker or adhesive. The backing 201 may be made of paper, plastic, orany other suitable material. FIG. 2B depicts the attachment 200 placedonto the wearable sensor 101, aligned over the electrodes 104, 105. Insome cases, the attachment includes a first side shaped to substantiallymatch the extended, rounded shape and configured to be attached to theexterior surface of the housing 102 of the wearable sensor 101. In someimplementations, the attachment includes a second side configured toremovably position the wearable sensor 101 on the scalp of a user. Alayered attachment 200 may be utilized, which is provided to a user thatmay remove a layer (the backing 201) to expose an adhesive containingthe hydrogel in wells aligned with the positioning of the electrodes(such as electrodes 104, 105). The attachment may then be placed on thesensor, (sensor 101) and thereafter on the user's skin to adhere asensors such as sensor 101 to the user's skin. Even though theattachment 200 may be illustrated as having rectangular shape, in any ofthe implementations disclosed herein, the attachment 200 can have ajellybean shape that matches the shape of the housing 102 illustrated inFIG. 1B.

FIG. 2C illustrates a sensor 101 placed onto a patient's scalp. Thesensor 101 is reversibly attached to the scalp with the attachment 200.The sensor 101 is located at an appropriate place on the user, forexample, on the scalp below the hairline, in order to sense and recordEEG data. The EEG data may be analyzed on-board, for example, viaapplication of an analysis or machine learning model stored in thesensor 101 or may be analyzed by a local device or remote device or acombination of the foregoing. By way of example, the sensor 101 maycommunicate using a wired or wireless protocol, for example, secureBluetooth Low Energy (BLE), to a local device using a personal areanetwork (PAN), such as communicating data to a smartphone or a tablet.Similarly, the sensor 101 may communicate with a remote device using awide area network (WAN), such as communicating EEG data to a remoteserver or cloud server over the Internet, with or without communicatingvia an intermediary device such as a local device.

The hydrogel is conductive and also provides enough adhesion to thescalp for effective recording of EEG for long wear times. Alternatively,the wearable sensor 101 may be adhered with a combination conductivehydrogel with an adhesive construct. After use, the attachment 200 cansimply be peeled off the wearable sensor 101 and thrown away. Prior tothe next use (for example after a wear period), a new attachment 200 canbe applied to the wearable sensor 101.

Consistent EEG signal data from person-to-person is made possible byusing a one-piece converted conductive hydrogel and adhesive construct200. The attachment 200 enables reversable adhesion of the wearablesensor 101 to the scalp. The design of the attachment 200 also reducesboth water infiltration and water evaporation from the hydrogel duringlong wear times. In some cases, the attachment 200 is made by laminatinga number of adhesive and non-adhesive layers with wells filled with ahydrogel and sandwiched between release liners. In some implementations,the attachment 200 is further packaged individually in air-tight andwater-tight pouches.

FIG. 3A illustrates an exploded view of an attachment 200. In theexample of FIG. 3A, attachment 200 includes a clear PET (polyethyleneterephthalate) liner 301, a hydrogel 302, a hydrogel 303, a transferadhesive 304, and a paper backing 201. The attachment 200 may include afirst side shaped to substantially match the extended, rounded shape andconfigured to be attached to the exterior surface of the housing 102 ofa wearable sensor 101 (sensor side). In some cases, the first side ofthe attachment 200 is configured to be attached to a bottom surface of awearable sensor 101. The attachment 200 may include a second sideconfigured to removably position the wearable sensor 101 on the scalp ofthe user (skin side). In some implementations, the clear PET liner 301is configured to be removed before the attachment 200 is placed on thescalp of a user. The hydrogel 302, 303 can facilitate repositioning thewearable sensor 101 on the scalp of the user.

FIG. 3B illustrates an exploded view of an attachment 200. In theexample of FIG. 3B, attachment 200 includes layers 1101-1106. The firstlayer 1101 can include a top liner which may be composed ofthermoplastic resin. The thermoplastic resin may be polyethyleneterephthalate (PET). In some implementations, second layer 1102comprises a cured hydrogel. The third layer 1103 can include a transferadhesive. In some implementations, fourth layer 1104 comprises anon-woven fabric. The non-woven fabric may be scrim-spun lace non-wovenpolyester. The fifth layer 1105 can include an adhesive. The adhesivemay be a thick double-sided adhesive foam. The sixth layer 1106 caninclude a bottom liner which may be composed of thermoplastic resin. Thethermoplastic resin may be PET.

In some cases, two or more of first layer 1101, second layer 1102, thirdlayer 1103, fourth layer 1104, fifth layer 1105, and sixth layer 1106are laminated to one another such that second layer 1102 is disposedbetween first layer 1101 and third layer 1103. In some implementations,first layer 1101 is removable. The sixth layer 1106 can be removable.Third layer 1103 and fifth layer 1105 can form apertures therein. Theapertures may align with electrodes of a sensor.

One or more of third layer 1103, fourth layer 1104, and fifth layer 1105can include a cured hydrogel. The hydrogel can be intermingled with thenon-woven fabric of fourth layer 1104. The hydrogel can be transitionedfrom a liquid or semi-liquid or gel form to a solid or semi-solid formusing a crosslinking process. The cross-linking process can be triggeredby application of one or more ultraviolet (UV) light and an electronbeam.

Provided herein are methods for preparing an attachment 200. In someimplementations, the method includes providing two or more layers, atleast one of the two or more layers including an aperture. Providing twoor more layers can include providing a fabric layer. The fabric can benon-woven. The method can further include stacking the two or morelayers. The method can include providing hydrogel to the apertures.Providing hydrogel can include pouring the hydrogel into the apertures.The method can further include fixing the layers. Fixing the hydrogelcan include curing the hydrogel via a UV light or an electron beamexposure.

FIG. 3C illustrates an exploded view of an attachment 200. In theexample of FIG. 3C, attachment 200 includes a clear PET liner 301,hydrocolloid material 305, a hydrogel 303, a double-coated tape 306, anda paper backing 201. The attachment 200 may include a first side shapedto substantially match the extended, rounded shape and configured to beattached to the exterior surface of the housing 102 of a wearable sensor101 (sensor side). The first side of the attachment 200 can beconfigured to be attached to a bottom surface of a wearable sensor 101.The attachment 200 may include a second side configured to removablyposition the wearable sensor 101 on the scalp of the user (skin side).In some cases, the clear PET liner 301 is configured to be removedbefore the attachment 200 is placed on the scalp of a user. Thehydrocolloid material 305 can facilitate repositioning the wearablesensor 101 on the scalp of the user.

FIG. 4 is a front perspective view of a charger 400. FIG. 4 illustratesa charger 400 in a closed configuration (left image) and in an openconfiguration (right image). The system for monitoring brain activitycan include a charger 400 comprising a charger housing 401. The chargerhousing 401 can be configured to receive and simultaneously charge powersources of at least two wearable sensors 101. For example, the charger400 may receive and charge power sources for two wearable sensors, orfour sensors, or more, 101 at the same time. In some implementations,the charger 400 includes multiple charging stations for wearable sensors101.

The wearable sensor 101 may be worn continuously for a period of daysbefore it needs to be removed, such as for charging an on-board powersource such as a rechargeable battery. To enable continued monitoring,the user may have two (or more) sets of wearable sensors 101 and willuse one (or more) while the other(s) is being recharged. Such anarrangement will allow for continuous EEG data capturing and monitoring.

FIG. 5 illustrates a kit or system 500 for monitoring brain activity. Insome cases, the kit or system 500 disclosed herein includes a pluralityof sensors 101. For example, the kit or system 500 may include 2sensors, 3 sensors, 4 sensors, 5 sensors, 6 sensors, 7 sensors, 8sensors, 9 sensors, or 10 sensors, and so on. The kit or system 500 mayinclude two sets of sensors, with a first set for use while a second setis charging. After the first set is used, the first set may be chargedwhile the second set is used. The kit or system 500 disclosed herein caninclude a plurality of attachments 200. For example, the kit or system500 includes 2 attachments, 3 attachments, 4 attachments, 5 attachments,6 attachments, 7 attachments, 8 attachments, 9 attachments, 10attachments, 11 attachments, 12 attachments, 13 attachments, 14attachments, 15 attachments, 16 attachments, 17 attachments, 18attachments, 19 attachments, or 20 attachments, and so forth. The numberof attachments in the plurality of attachments may be greater than anumber of wearable sensors included in the plurality of wearablesensors. The number of attachments 200 in the plurality of attachments200 can include the number of wearable sensors 101 in the plurality ofwearable sensors 101 multiplied by a number of days during which theplurality of wearable sensors are configured to record the brainactivity of the user. For example, if there are four wearable sensors101 configured to record the brain activity of the user for 7 days, thekit or system would include at least 28 attachments 200. For example, ifthere are four wearable sensors 101 configured to record the brainactivity of the user for 3 days, the kit or system would include atleast 12 attachments 200. The kit or system can include additionalattachments 200 beyond the number of wearable sensors 101 in theplurality of wearable sensors 101 multiplied by a number of days duringwhich the plurality of wearable sensors 101 are configured to record thebrain activity of the user.

Disclosed herein are methods for monitoring brain activity. The methodscan include detaching at least one wearable sensor 101 of a plurality ofwearable sensors 101 configured to record a brain activity of a user. Insome cases, each wearable sensor 101 includes a housing 102 having anextended, rounded shape. Each wearable sensor 101 can include at leasttwo electrodes 104, 105 positioned on an exterior surface of the housing102 and configured to detect EEG signals indicative of the brainactivity of the user.

The methods can further include replacing a first attachment 200 of aplurality of attachments 200 with a second attachment 200 of theplurality of attachments 200. The first and second attachments 200 caninclude a first side shaped to substantially match the extended, roundedshape of the housing 102. The first side can be configured to beattached to the exterior surface of the housing 102 of the at least onewearable sensor 101. The first and second attachments 200 can include asecond side configured to removably position the at least one wearablesensor 101 on a scalp of the user. In some cases, the number ofattachments 200 in the plurality of attachments 200 is greater than anumber of wearable sensors 101 in the plurality of wearable sensors 101.

The method can further includes reattaching the at least one wearablesensor 101 to the scalp of the user by adhering the second side of thesecond attachment 200 to the scalp of the user. The method may furtherincludes resuming recording of EEG signals indicative of the brainactivity of the user.

EEG System Setup and Provisioning

The systems and methods provided herein can include software to assist auser in setting up the system. The user may be a healthcare provider ora patient.

FIG. 6 is an illustration of an EEG monitoring system 600. The system ofFIG. 6 includes a plurality of wearable sensors 601 configured to recorda brain activity of a patient. Each wearable sensor 601 can include atleast two electrodes configured to detect signals indicative of thebrain activity of the user when the wearable sensor is positioned on ascalp of the user. Each wearable sensor 601 can further includes anelectronic circuitry configured to, based on the signals detected by theat least two electrodes, determine data associated with the brainactivity of the user and wirelessly transmit the data associated withthe brain activity of the user to one or more portable computing devices602.

In some cases, the system further includes a non-transitory computerreadable medium storing instructions that, when executed by at least oneprocessor the one or more portable computing devices 602, cause the atleast one processor to facilitate activation of the plurality ofwearable sensors 601; instruct the user to position the plurality ofwearable sensors 601 on the scalp of the user using a plurality ofattachments configured to removable attach the plurality of wearablesensors 601 to the scalp of the user; and record the data associatedwith the brain activity of the user transmitted by the plurality ofwearable sensors 601.

The portable computing device 602 can include communicationfunctionality, such as wireless communication functionality. Theportable computing device 602 can be configured for being worn by theuser. The portable computing device 602 can include a smartwatch, whichmay have a display. The portable computing device can 602 can include asmart band, smart jewelry, or the like, which may not have a display.The portable computing device 602 can include a tablet or anothercomputing device, such as medical grade tablet. Such portable computingdevice 602 may include a display that is larger than the display of asmartwatch. The portable computing device 602 may connect to a remoteserver or cloud server through connection with a phone application, ormay connect to a remote server or cloud server directly (for example,the portable computing device 602 may include a cellular communicationchip that enables wireless communication with a remote server or cloudserver).

Provided herein are systems for monitoring brain activity. In someimplementations, the systems include a plurality of wearable sensors 601configured to detect EEG signals indicative of a brain activity of apatient. Each wearable sensor of the plurality of wearable sensors 601can include at least two electrodes configured to monitor the EEGsignals when the wearable sensor is positioned on a scalp of thepatient. Each wearable sensor of the plurality of wearable sensors 601can include an electronic circuitry configured to process the EEGsignals monitored by the at least two electrodes. In some cases, systemsdescribed herein further include a non-transitory computer readablemedium storing executable instructions which may be executed by at leastone processor of a portable computing device 602.

FIGS. 7A-7L provide example processes and screens (or modals) forwearable sensor 601 set-up, activation, placement, and verification.These can be implemented by or executed on a portable computing device602, such as at least one processor of the portable computing device.While some illustrations may depict a wearable sensor 601 with a certainshape or configuration, this is meant as an illustrative example and notby way of limitation. For example, the processes and screens describedherein may be used to guide a user through set-up, activation,placement, and verification of wearable sensors 601 having a variety ofconfigurations, such as wearable sensors 601 having an extended, roundedshape as described herein. In some cases, through each of the screens,the system displays the next screen in response to user input, forexample a user may press a button (such as a button displayed on a touchscreen or a physical button on a portable computing device 602) to go tothe next screen showing the next instructions.

FIG. 7A illustrates a flow diagram of a process for set-up of an EEGrecording session. The process may include guiding a user through stepswhich may include starting a new session 610, inputting basic settings620, inputting advanced settings 630, and inputting patient information640. The set-up process can continue to sensor identification 662 or canbe restarted 650. During set-up, a series of screens may be displayed onthe portable computing device 602. In some cases, a start new sessionscreen 610 is displayed. A user may interact with a screen, such aspressing a start button or pressing a settings button, to start set-upof a new session or to open a settings menu. The system can verifywhether IT contact information has already been entered, and if it hasalready been entered, the system bypasses the start new session screen610 and automatically transitions to basic settings screen 620. Whenbasic settings screen 620 is displayed, a user may enter basic settingssuch as hospital IT contact information. In some implementations, thesystem stores the user input. When basic settings screen 620 isdisplayed, the system may verify that communication (such as, Bluetooth)is enabled on the portable computing device 602 the user is using toperform session set-up. If communication is not enabled, the system mayrequest the operating system of the portable computing device 602 toenable communication or may prompt the user with a native modalinforming the user that the app has requested communication be turnedon. In response to user input, the system can then displays a start newsession screen 610. User input to proceed to a start new session screen610 may be allowed only if IT contact information has been entered. Whena user enters a password, advanced settings screen 630 can be displayed.

When advanced settings screen 630 is displayed, the system may receiveand store user input related to advanced settings. Advanced settings mayinclude server URL and server path. Advanced settings may also includetoggling on/off a kiosk mode, allowing patient barcode scan, andallowing device barcode scan. Advanced settings may also include amanual entry for a patient barcode and/or a device barcode. In somecases, in response to user input, the system then displays a start newsession screen 610. User input to proceed to a start screen may beallowed only if IT contact information has been entered. When patientinformation screen 640 is displayed, the system may receive and storeuser inputs related to patient information. A patient barcode may bescanned with a camera of the portable computing device 602 or a patientbarcode may be entered manually. Patient information may also include apatient's first and last name. In response to user input, the system canthen display a sensor identification screen 660. User input to proceedto a sensor identification screen 660 may be allowed only if patientinformation has been entered.

In response to user input, the process can then displays a restartsession modal 650. The screen may ask a user to confirm whether the userwants to restart the session set-up. In response to a user inputconfirming restart, the system can clear all patient and sensor dataalready saved in a memory and the process may be restarted in 610. Inresponse to user input canceling restart, the restart session modal 650can be dismissed. In step 662, a user has completed the session set-upprocess and begins sensor identification, as further described in FIG.7B.

The executable instructions can cause at the least one processor to,prior to providing instructions to position the wearable sensor in thelocation on the scalp of the user, provide instructions to scan or enterthe identification information for the wearable sensor 601. FIG. 7Billustrates an example sensor identification screen 660. The sensoridentification screen 660 may include a display of a scan captured witha camera to enable a user to capture a barcode via camera of a portablecomputing device 602. The system may automatically look for barcodedesigns in the image captured by the camera. The system may storeinformation related to sensor identification. The sensor identificationscreen 660 may include a display indicating whether a sensor IDcorresponding to each wearable sensor 601 of the plurality of wearablesensors 601 has been entered. In the example of sensor identificationscreen 660, a circle corresponding to each wearable sensor of theplurality of wearable sensors 601 is filled in once sensoridentification information for that wearable sensor 601 has beenentered. In response to a user input (for example, selecting analready-entered sensor), the system may overwrite sensor identificationinformation relating to an already-entered wearable sensor 601 with newsensor identification information. The system may receive and storesensor identification information manually entered by a user. Inresponse to user input, the system can then displays a restart sessionmodal 650. The system can automatically display the next screen oncesensor identification information for each wearable sensor 601 of theplurality of wearable sensors 601 has been entered/scanned.

FIG. 7C illustrates an example sensor initialization screen. The screenmay guide a user to remove the contents of a pouch in preparation forplacement of one or more wearable sensors 601, such as one or morewearable sensors 601, one or more adhesives, and one or more alcoholwipes. The screen may also guide a user to activate one or more wearablesensors 601. A user may activate a wearable sensor 601 by pressing abutton on top of the wearable sensor 601. The screen may include adisplay indicating whether each wearable sensor 601 of the plurality ofwearable sensors 601 has been activated. In the example of FIG. 7C, acircle corresponding to each wearable sensor 601 of the plurality ofwearable sensors 601 is filled in once that wearable sensor 601 has beenactivated. In response to a user input (for example, selecting analready-activated wearable sensor 601), the system may overwrite sensoractivation information relating to an already-activated wearable sensor601 with new sensor activation information. In some cases, the systemstarts a wireless scan (such as via Bluetooth) for the wearable sensors601. The wireless scan may continue until recording is started or sensorset-up session is ended. When a wearable sensor 601 detected by awireless scan, a local state can be updated with sensor information ifthe detected wearable sensor 601 is among the wearable sensors 601previously identified (such as in the process described in connectionwith FIG. 7B). The system can wirelessly connect (such as via Bluetooth)with each activated wearable sensor 601, verifies connection capability,and verifies the wearable sensor 601 is working. After each of theplurality of wearable sensors 601 connect to the system, the system canwirelessly command the plurality of wearable sensors 601 to enter asynchronization state and then synchronization information (such as async-time-set advertisement) is wirelessly sent to the plurality ofwearable sensors 601, as further described in connection with FIG. 10Aor 10B. Wireless connection can then be re-established with eachwearable sensor 601 of the plurality of sensors 601. The system cancommand each wearable sensor 601 of the plurality of sensors 601 toenter a sleep state. In the sleep state, a sensor 601 may not monitorEEG signals or transmit data. Once each wearable sensor 601 of theplurality of sensors 601 is activated, a user may enter an input toadvance to the next step of the set-up such as FIG. 7E. In response touser input, the system can then display a restart session modal 650. Ifa set amount of time (such as one minute, two minutes, etc.) passes frombeginning of the sensor activation process or from a sensor connectionwithout a new wearable sensor 601 connecting, the system may display aconnection time-out modal, such as the connection time-out modal of FIG.7D.

FIG. 7D is an example connection time-out modal. The connection time-outmodal may display errors and trouble-shooting information related tosensor activation. The system may allow a user to snooze (dismiss for aset amount of time) the connection time-out modal, replace one or morewearable sensors 601, or end the session. If a user selects to end thesession, the system may display an end session modal. If a user selectsto replace one or more wearable sensors 601, a replace sensor modal maybe displayed. If a user selects to snooze, the connection time-out modalmay disappear. In some cases, the snooze interval (amount of time) issaved to a memory store. The user may input the snooze interval. Thesystem can display the connection time-out modal again after the snoozeinterval has elapsed. If a wearable sensor 601 is activated andconnects, the system may automatically dismiss the connection time-outmodal.

FIG. 7E is an example sticker (or attachment) placement screen.Providing instructions to position the wearable sensor 601 in thelocation on the scalp of the user can include instructing a use of aplurality of attachments configured to removably attach the wearablesensor 601 to the scalp of the user. For example, a sticker placementscreen may guide a user to open an adhesive pouch and remove anadhesive. The sticker placement screen can guide a user to remove a film(also referred to as a liner or backing) from the adhesive. A stickerplacement screen may instruct a user to apply the adhesive to thewearable sensor 601 (such as with the correct alignment over theelectrodes). A sticker placement screen may guide a user to remove asecond film from the adhesive in preparation for sticker placement. Inresponse to user input, the system can then display a restart sessionmodal 650. A user may enter an input to cause the system to advance tothe next step of the set-up, such as FIG. 7F.

The executable instructions can cause the at least one processor to:provide instructions to position a wearable sensor 601 of the pluralityof wearable sensors 601 in a location of a plurality of locations on thescalp of the user and activate the wearable sensor 601; verify anidentification of the wearable sensor 601; responsive to verification ofthe identification of the wearable sensor 601, verify an impedance ofthe wearable sensor 601; and responsive to verification of the impedanceof the wearable sensor 601, provide instructions to position andactivate another wearable sensor 601 of the plurality of wearablesensors 601 and perform verification of an identification and animpedance of the another wearable sensor 601.

FIG. 7F depicts an example sensor placement and activation screen.Sensor may be placed in four locations on the scalp, such as behind leftear (LE), behind right ear (LE), left front side of the forehead (LF),and right front side of the forehead (RF). A sensor placement andactivation screen may guide a user to wipe the location on the user'sbody with an alcohol swab provided in a kit. For example, the locationmay be behind an ear or on another location on the scalp. The screen maydisplay a graphic to show the user which location on the user's body toclean with the swab. A sensor placement and activation screen may guidea user to place a wearable sensor 601 on the patient's body in alocation (for instance, the scalp). In some cases, providinginstructions to position the wearable sensor 601 includes displayinginstructions on a screen of the portable computing device 602. Forexample, the screen may display a graphic to show the user where toplace the wearable sensor 601.

In some implementations, providing instructions to position the wearablesensor 601 comprises displaying the location on the screen of theportable computing device 602 and instructions to activate the wearablesensor 601. For example, a sensor placement and activation screen mayinstruct a user to press a button on the wearable sensor 601 afterplacement in the directed location to activate the wearable sensor 601.In some cases, wireless connection (such as via Bluetooth) is made withpreviously connected wearable sensors 601. The system can verify theidentity of an activated wearable sensor 601 to confirm that theactivated wearable sensor 601 is a wearable sensor 601 that wasidentified by the user, for example scanned in the process described inconnection with FIG. 7B or activated in the process described inconnection with FIG. 7C. The screen may include a display indicatingwhether each wearable sensor 601 of the plurality of wearable sensors601 has been activated. In the example of FIG. 7F, a circlecorresponding to each wearable sensor of the plurality of wearablesensors 601 is filled in once that wearable sensor 601 has beenactivated. The screen may include a display indicating whether eachwearable sensor 601 of the plurality of wearable sensors 601 remainswirelessly connected to the portable computing device 602, and maydisplay a notification, graphic, and/or alert if an activated wearablesensor 601 becomes disconnected. In response to a user input, the systemcan display a restarts placements modal, such as the restart placementmodal of FIG. 7H.

Once a wearable sensor 601 of the plurality of wearable sensors 601 isactivated, the system may prompt as user to initiate an impedance testof the wearable sensor(s) 601. In the example of FIG. 7F, a user maypress a test button once the wearable sensor 601 is placed andactivated. In some cases, when a user initiates the impedance test, acommand is wirelessly sent (such as via Bluetooth) to a wearable sensor601 to run an impedance check. In some implementations, the systemschecks whether an impedance measurement from a wearable sensor 601satisfies a pre-determined threshold, such as 100 kOhm or more or 500kOhm or more.

In some implementations, if the impedance measurement does not satisfy apre-determined threshold, the system may provide an indication to theuser, such as display an appropriate screen informing of poor electrodecontact. In some implementations, the executable instructions furthercause the at least one processor to, responsive to not verifying theimpedance of the wearable sensor 601, repeat one or more of: providinginstructions, verifying the identification, and verifying the impedancefor the wearable sensor 601. In some cases, repeating includes providinginstructions to reposition the wearable sensor 601 and verifying theimpedance of the sensor. In some cases, responsive to not verifying theimpedance of the wearable sensor 601 for a second time, the executableinstructions cause the processor to restart providing instructions,verify the identification, and verify the impedance for the plurality ofwearable sensors 601. In some implementations, when restarted, thesystem wipes all saved sensor placements data at all locations andbegins providing instructions, verifying the identification, andverifying the impedance for the plurality of wearable sensors 601 fromthe first of the plurality of wearable sensors 601. If the impedance isverified (for example, the impedance measurement satisfies thepre-determined threshold), the system can return to the placement screenwith instructions to place, activate, and test the next wearable sensor601 in the sequence of the plurality of sensors 601.

The executable instructions can further cause the at least one processorto provide an alert in response to detecting that at least two wearablesensors 601 of the plurality of wearable sensors 601 have beenpositioned in the same location on the scalp of the user or otherposition or activation in error. This can include responsive todetecting that at least two wearable sensors 601 of the plurality ofwearable sensors 601 have been positioned in a particular (i.e.,incorrect or unidentified) location of the plurality of locations on thescalp of the user, restart providing instructions, verifying theidentification, and verifying the impedance for the plurality ofwearable sensors 601. Detecting that the at least two wearable sensors601 have been positioned in the same location can include detecting thatmultiple wearable sensors 601 have been activated substantiallysimultaneously. This can be performed as follows. The executableinstructions can cause the at least one processor to sequentiallyprovide instructions to position and activate, verify an identification,and verify an impedance of each wearable sensor 601 of the plurality ofwearable sensors. One wearable sensor 601 of the plurality of wearablesensors 601 can be placed, activated, and tested for impedance for onelocation, one at a time (in other words, in a sequence). For example,the user is instructed to place a first wearable sensor 601 in a firstlocation, activate the first wearable sensor 601, and initiate animpedance test for the first wearable sensor 601; then the user isinstructed to place a second wearable sensor 601 in a second location,activate the second wearable sensor 601, and initiate an impedance testfor the second wearable sensor 601; and so on. When a user initiates animpedance test, if multiple wearable sensors 601 have been activatedbefore the impedance test, the system can display a multiple sensorsactivated alert modal, such as the multiple sensors activated alertmodal of FIG. 7G. As another example, if multiple wearable sensors 601have been activated (for instance, in FIG. 7F) before an impedance testis initiated, the system can display the activated alert modal. In somecases, determining whether multiple wearable sensors 601 have beenactivated substantially simultaneously can be performed based ondetermining whether at least two sensors have been activated within athreshold time duration (such as, 10 seconds or less, 30 seconds or lessor more, or the like).

FIG. 7G is an example multiple sensors activated alert modal. In someimplementations, the multiple sensors activated alert modal notifies auser that more than one wearable sensor 601 has been activated for alocation and instructs the user to only place and activate one wearablesensor 601 at a time. The multiple sensors activated alert modal caninstruct a user to wait. When a multiple sensors activated alert modalis displayed, the system can connect to the wearable sensors 601, andcommands all connected wearable sensors to enter a sleep state. A usermay select to dismiss or snooze the multiple sensors activated alertmodal. When a user selects to dismiss or snooze the multiple sensorsactivated alert modal, the system can command wearable sensors 601 thatare connected and that have not been correctly placed to enter aninactive state. When a user selects to dismiss or snooze the multiplesensors activated alert modal, the system once again may display asensor placement and activation screen.

FIG. 7H shows an example restart placement modal. In some cases, therestart placement modal prompts a user to confirm or cancel whether torestart the placement process. When placement is restarted, the systemcan wipe all saved sensor placements data at all locations. Whenplacement is restarted, the system can command the sensors to enter asleep state. When placement is restarted, the system can display thesticker placement screen, such as the sticker placement screen of FIG.7E. When restart is canceled, the restart placement modal can bedismissed.

FIG. 7I shows an example verify session screen. This screen may bedisplayed after all the sensors have been placed and activated. Thesystem can display a screen so that a user can verify each sensoridentification matches the sensor identification recorded in the systemfor each location (for instance, recorded in FIG. 7B). In the example ofFIG. 7I, the portable computing device 602 displays a diagram of thehead with squares representing sensor placements (such as sensor ID) andsensor state (such as connected). The portable computing device 602 candisplay a notification if there is an issue, such as an activation,identification, or impedance issue, with one or more of the wearablesensor 601 placements. For example, the graphical representation of asensor with an issue may flash red/blue, such as an alert modal appearedand was snoozed. In response to user input such as clicking on arepresentation of a wearable sensor 601 on the screen, the system candisplay a sensor modal with sensor information. In response to userinput (such as selecting to cancel), the system can display an endsession modal. In response to user input, the system can initiate therecording session.

After verification has been completed, EEG recording session may bestarted. As part of verification of subsequent to the verification,wearable sensors 601 may be synchronized, as further described inconnection with FIG. 10A or 10B. FIG. 7J illustrates an example screenthat informs the user that synchronization is being performed. Theexecutable instructions can further cause the at least one processor to,responsive to verification of the identity and impedance of eachwearable sensor 601 of the plurality of wearable sensors 601, record theprocessed EEG signals wirelessly transmitted by the plurality ofwearable sensors 601. FIG. 7K is an example active recording screen. Thesystem can store the recording started time in the memory. Wirelessscans (such as Bluetooth scan) can be stopped. A wireless scan may startagain if a wearable sensor 601 disconnects. Real-time data notificationscan be enabled for all wearable sensors 601. The portable computingdevice 602 may display a notification if there is an issue, such as anactivation, identification, or impedance issue, with one or more of thewearable sensor 601 placements. For example, the graphicalrepresentation of a wearable sensor 601 with an issue may flashred/blue, such as an alert modal appeared and was snoozed. In responseto user input such as clicking on a representation of a wearable sensor601 on the screen of a portable computing device 602, the system candisplay a sensor modal with sensor information.

The portable computing device 602 can send a message containinginformation for session events for recording started and recording endedto a remote server or cloud server over the Internet. A recordingstarted or recording ended message can contains information such aspatient information, wearable sensor(s) 601 information, recording starttime, and/or recording end time. The portable computing device 602 canreceive messages containing real-time data/events from the plurality ofwearable sensors 601 and communicates messages containing real-timedata/events to a remote server or cloud server over the Internet. Theportable computing device 602 can display a notification on the activerecording screen if there is an issue, such as an activation,identification, or impedance issue, with one or more of the wearablesensor 601 placements. In the example of FIG. 7K, the portable computingdevice 602 displays a diagram of the head with squares representingwearable sensor 601 placements (such as sensor ID) and sensor state(such as connected). A user may interact with the display to end therecording session. The portable computing device 602 can displaydiagnostic information as well as session ID and portable computingdevice 602 ID.

In response to user input (such as clicking “end recording”), the systemcan display an end recording modal. After a predefined amount of timehas elapsed (for example 48 hours) after beginning of recording, thesystem can automatically end the recording session and displays afinalizing session screen (not shown).

FIG. 7L illustrates a flow diagram of a process for guiding a userthrough sensor set-up and provisioning. As described herein, the processmay include guiding a user through the steps of sensor(s) activation710, sensor(s) placement 720, recording data 730, and self-diagnostics740.

In some cases, sensor(s) activation 710 includes using the applicationto guide a user to scan a barcode associated with a wearable sensor 601with the camera feature of a portable computing device 602. Sensor(s)activation 710 can include using an application to guide a user tomanually enter a barcode associated with a wearable sensor 601 using aportable computing device 602. The application can create a passcode foreach sensor based on the scanned or entered barcode. The passcode may beunique and ensure that only 4 provisioned wearable sensors 601 set up ina session can communicate with the portable computing device 602. Theapplication can guide a user to press and/or hold a button on eachwearable sensor 601 to activate the wearable sensor 601.

The application can display information related to sensor activation ona display of a portable computing device 602. Information related tosensor activation may include whether each wearable sensor 601 has beenactivated. FIG. 7F illustrates an example screen associated withsensor(s) activation 710 and sensor placement 720 displayed on aportable computing device 602. In some cases, sensor(s) placement 720includes using the application to guide a user to place wearable sensors601 on the scalp of a patient. The application can walk the user throughmultiple images, one for each wearable sensor 601, and shows the userthe location that the user should place each sensor.

Placement of multiple wearable sensors 601 can follow a pattern, such asleft to right. A display may provide a graphical instruction such asthat illustrated in FIG. 7F. An emergent care screening may be conductedon a patient using four wearable sensors 601, two on the forehead andtwo behind the ears. With this four-sensor arrangement, a desiredmontage may be created, for example via subtracting the EEG signal fromone sensor relative to another to create a 10-channellongitudinal-transverse montage, as described in U.S. Pat. No.11,020,035 and U.S. Patent Publication No. 2021/0307672, each of whichis incorporated by reference in its entirety.

The instructions can further cause the processor to activate a wearablesensor 601 to run an impedance test to ensure the wearable sensor 601 isattached to the skin and has adequate electrode contact. The impedancetest may include pushing a current and measuring a voltage.

Recording data 730 can include recording EEG data. Recording data 730may be initiated in response to user input (such as pressing a button)on an application running on a portable computing device 602. Theapplication on the portable computing device 602 can display a screenindicating that recording is in session, such as recording screen ofFIG. 7K.

In some cases, recording data 730 includes determining the state of thewearable sensor 601. States may include a waiting state (on but notrecording), a recording state, a charging state, a communicating state,etc. State information may include whether and when the internal clockof the sensor has been set, a number of recordings/pages of recordings,battery charging status (fully charged, partially charged, etc.).

In some implementations, the instructions further cause the at least oneprocessor to cause a display of a portable computing device 602 todisplay push notifications. The push notifications may be based on stateinformation. The push notifications may be based on change in state.

The instructions can further cause the at least one processor to runself-diagnostics 740 on the system, including on the plurality ofwearable sensors 601. Self-diagnostics 740 can include identifying aproblem associated with one or more wearable sensors 601, sensor data,and/or communication to or from the wearable sensors 601.Self-diagnostics 740 can include diagnosing a problem. In some cases,the problem includes system issues. System issues may include a batteryissue, a wearable sensor 601 being disconnected, connection time-out,poor electrode contact, cellular signal error, Bluetooth error, portablecomputing device 602 Wi-Fi failure, remote server or cloud serverissues, or that the recording had not started. The problem may includesensor/data issues. Sensor/data issues may include in-phase cancellationof electrographic activity (due to close spacing of electrodes), muscleartifacts, or saturation.

Provided herein are methods for monitoring brain activity of a patient.The methods include, by at least one processor of a portable computingdevice 602, providing instructions to position a plurality of wearablesensors 601 in a plurality of locations on the scalp of the user. Theplurality of wearable sensors 601 can be configured to detect EEGsignals indicative of a brain activity of the patient, each wearablesensor 601 including at least two electrodes configured to monitor theEEG signals when the wearable sensor 601 is positioned on the scalp ofthe user and an electronic circuitry configured to process the EEGsignals monitored by the at least two electrodes. The method can furtherinclude providing an alert in response to detecting that at least twowearable sensors 601 have been positioned in a particular location ofthe plurality of locations on the scalp of the user. The method canfurther includes, in response to verifying that the plurality ofwearable sensors 601 has been correctly positioned in the plurality oflocations on the scalp of the user, recording the processed EEG signalswirelessly transmitted by the plurality of wearable sensors 601.

Advantageously, guiding a user using a portable computing device 602 canallow EEG setup and monitoring by non-experts, such as clinicians in alocal or rural hospital unaccustomed to EEG monitoring.

Handing Off Control

It can be advantageous to hand off control of EEG sensors betweenportable computing devices. For example, EEG sensor setup can beperformed on a first portable computing device (such as, a tablet) andsubsequently transferred to a second computing device (such as, a watch,smart band, smart jewelry, or the like). The second portable computingdevice can be a wearable computing device without a screen or with ascreen that is smaller than that of the first computing device. Thefirst portable computing device can be configured to facilitateactivating and positioning the EEG sensors on the scalp of the patientand the second portable computing device can be configured to facilitatemonitoring of the brain activity of the patient and detecting one ormore disorders. Transfer of control to the second device mayadvantageously allow EEG monitoring with a smaller and cheaper user-worncomputing device.

The second portable computing device and one or more EEG sensors cancommunicate directly or through another computing device, such as aphone. The second portable computing device can communicate with aremote server or cloud server through another computing device ordirectly (such as, with a cellular communication chip).

The first portable computing device can have a prescriptive function totrain, prescribe, provision or otherwise determine how the EEG systemwill be used during ambulatory wear. This could include parentalcontrols, duration and location of wear, and other prescriptivefunctions. The second portable computing device can have an endemicfunction and its interaction with the patient differs depending on theprescription and provisioning by the first portable computing device.

FIG. 8 is an illustration of an EEG sensor control transfer environment800. The sensor control transfer environment 800 includes a plurality ofwearable sensors 802 (which can be similar to the sensors 101), a firstportable computing device 832, and a second portable computing device834, which can be configured to be worn by a patient. In the example ofFIG. 8 , the plurality of wearable sensors 802 and the first portablecomputing device 832 communicate to facilitate setup 810 of theplurality of wearable sensors 802. The first portable computing device832 and the second portable computing device 834 communicate tofacilitate hand-off 820 of control of the plurality of sensors 802 fromthe first portable computing device 832 to the second portable computingdevice 834. After hand-off 820, the second portable computing device 834communicates with the plurality of wearable sensors 802 to receive andsend data 830. Data 830 may include sensor data such as EEG measurementsor sensor status, and also may include commands to the plurality ofsensors 802 from the second portable computing device 834 such as tobegin recording data.

Provided herein are methods for monitoring of brain activity. In somecases, the method includes activating (for example, setup 810) aplurality of wearable sensors 802 configured to detect EEG signalsindicative of a brain activity of a patient and positioned in aplurality of locations on a scalp of the patient. Each wearable sensor802 can have at least two electrodes configured to monitor the EEGsignals when the wearable sensor 802 is positioned on the scalp of thepatient, and an electronic circuitry configured to process the EEGsignals monitored by the at least two electrodes and wirelessly transmitprocessed EEG signals to a first portable computing device 832.Activating can include following instructions displayed on a display ofthe first portable computing device 832 (for example, setup 810).

The method can further includes, subsequent to the activation of theplurality of wearable sensors 802, transferring control (for example,hand-off 820) of the plurality of wearable sensors 802 to a secondportable computing device 834. The second portable computing device 834can be configured to be worn by the patient to permit the secondportable computing device 834 to wirelessly receive the processed EEGsignals (for example, data 830). The second portable computing devicemay not include a display or may include a display that is smaller thanthe display of the first portable computing device 832.

The first portable computing device 832 can be configured to facilitateactivating and positioning the plurality of wearable sensors 802 on thescalp of the patient (for example, setup 810) and the second portablecomputing device 834 is configured to facilitate monitoring of the brainactivity of the patient (for example, receiving data 830) and detectingone or more disorders. Transferring control can cause the first portablecomputing device 832 to cease wirelessly receiving the processed EEGsignals. The first portable computing device 832 can be a tablet and thesecond portable computing device 834 can be a smartwatch.

The method can further include, prior to transferring control to thesecond portable computing device 834, authenticating the second portablecomputing device 834. Authenticating the second portable computingdevice 834 can include scanning a QR code of the second portablecomputing device 834. For example, a first portable computing device 832may instruct a user to scan a QR code displayed on a second portablecomputing device 834 using a camera of the first portable computingdevice 832. A first portable computing device 832 may instruct a user tomanually enter a code associated with a second portable computing device834 (such as a code displayed on a second portable computing device834).

The method can further includes, responsive to an alert displayed on thedisplay of the second portable computing device 834, causing the secondportable computing device 834 to display instructions for resolving thealert and following the instructions to resolve the alert.

FIG. 9A illustrates a process for data recording and sensor management,which can be executed by a second portable computing device 834. Theprocess is illustrated as a sequence of screens that can be displayed onthe second portable computing device 834 (or otherwise reproduced, forinstance, auditorily reproduced by the second portable computingdevice). Through each of the screens, the system can display the nextscreen in response to user input, for example a user may press a button(for instance, a virtual control on the screen or a physical button onthe second portable computing device 834) to go to the next screenshowing the next instructions. The user can be a patient. The secondportable computing device 834 can display a screen 916 showing thatrecording of EEG data by the wearable sensors is in session. The secondportable computing device 834 can display an alert, for example anaction required screen 910. The action required screen 910 can indicatethat one or more actions are required, for example due to one or moredetected issues. If multiple actions are required, the action requiredscreen 910 may display a number representing the number of actionsrequired based on a number of detected alerts. In some cases, auditory,visual, or haptic feedback by the second portable computing device 834alerts a user that an action is required. Auditory, visual, or hapticfeedback on one or more wearable sensors 802 can alert a user that anaction is required.

The application display on the second portable computing device 834 candisplay specific information about one or more detected alerts. Specificinformation about the alert can be displayed in response to user input(such as a tap) on the action required screen 910. For example, thedisplay may indicate that a signal issue is detected (such as a signalissue alert 912) or that a sensor is disconnected (such as a sensordisconnected alert 914). Signal issue alert 912 can indicate that poorelectrode contact by one or more wearable sensors has been detected.This can be determined based impedance, as described herein. The numberof times that a signal check has been attempted may be tracked (such as,stored in a memory), and an alert is generated responsive to the numberof times reaching a threshold (such as, 1 time, 2 times, 3 times, 4times, 5 times, or more). Signal issue alert 912 can indicate whichwearable sensor(s) 802 has a signal issue. Sensor disconnected alert 914can indicate that one or more wearable sensor(s) 802 have stoppedwireless communication with the second portable computing device 834.The system can wirelessly scan (such as, with Bluetooth) for wearablesensors 802. Current sensor state and disconnection count can be tracked(such as, are stored to the memory), and an alert is generatedresponsive to the number of times reaching a threshold (such as, 1 time,2 times, 3 times, 4 times, 5 times, or more).

In response to user input, the system can display instructions for howto troubleshoot or reconnect one or more wearable sensors 802. Inresponse to user input, a screen can be displayed, which may instruct auser to confirm whether or not the wearable sensor 802 is attached. Inresponse to user input, signal issue alert 912 or sensor disconnectedalert 914 can be snoozed or dismissed. Dismissing or snoozing signalissue alert 912 or sensor disconnected alert 914 may be disabled. Aftera predefined amount of time has elapsed, signal issue alert 912 orsensor disconnected alert 914 can be automatically timed out anddismissed. In response to user input, a replace attachment screen 918can be displayed to provide instructions on troubleshooting signal issuealert 912 and sensor disconnected alert 914, as further describedherein. After detecting an alert, the second portable computing device834 can pause recording of EEG data when an alert is detected.

The instructions can further cause the at least one processor to cause adisplay of a first computing device 832 or a second portable computingdevice 834 to display an instruction corresponding to a self-diagnosedproblem. For example, an instruction may include moving a wearablesensor 802, replacing an attachment (for example, screen 918 instructinga user to replace an attachment), charging the battery of a wearablesensor 802, charging the battery of a first portable computing device832 or a second portable computing device 834, rebooting a wearablesensor 802 or a first or second portable computing device 832, 834, etc.

Once a user completes the instructed steps, the alert can be dismissedand recording of EEG data can be resumed. The second portable computingdevice 834 can display the recording in session screen 916 once an alerthas been resolved. Recorded EEG data can be sent to a remote server orcloud device. The remote server or cloud device can combine and/orprocesses the recorded data to determine presence of one or morephysiological conditions.

The instructions can be associated with replacing an attachmentconfigured to removably attach a wearable sensor 802 of the plurality ofwearable sensors 802 to the scalp of the user. FIG. 9B illustratesexample screens illustrating a process for instructing a user to replacean attachment. Through each of the screens, the system can display thenext screen in response to user input, for example a user may press abutton (as described in connection with FIG. 9A)) to go to the nextscreen showing the next instructions. An alert screen 918 can instruct auser that an attachment should be replaced. If there has been a sensorfailure, the system can display screen 922 and instruct a user to removea wearable sensor 802 from a location on the scalp.

The second portable computing device 834 can display a screen 920instructing a user to confirm whether to proceed with attachmentreplacement. A user may confirm by pressing a button (as described inconnection with FIG. 9A). In response to user input cancelingreplacement of the attachment (such as selecting a cancel user interfaceoption) or in response to the passing of a predefined amount of time,screen 920 may be dismissed. In response to user input confirmingproceeding with replacement, the system can display screen 922 andinstructs a user to remove a wearable sensor 802 from a location on thescalp. The second portable computing device 834 can command a wearablesensor 802 to enter a sleep state.

Responsive to the instructions to replace attachment, the user canremove the wearable sensor 802, replaces the attachment with anotherattachment, and repositions the wearable sensor 802 on the scalp of theuser. The second portable computing device 834 can instruct a user toremove a wearable sensor 802 from a location on a scalp. In screen 922,for example, the screen of the second portable computing device 834displays a graphical representation of the location of the wearablesensor. The system can use the known sensor location (determined duringset-up, as described herein) to set a screen showing a specificlocation. Information for the sensor location can be stored in thememory.

The second portable computing device 834 can instruct a user to cleanthe area of the indicated location on the scalp, for example, bydisplaying a screen 924. The second portable computing device 834 caninstruct a user to place a new attachment onto the wearable sensor 802,for example, by displaying a screen 926. The second portable computingdevice 834 can instruct a user to place the wearable sensor 802 on alocation on the scalp, for example, by displaying screen 928. Screen 928can include instructions to remove a second liner to expose a secondadhesive side of an attachment. The system can use a knownsensor/location from the memory to set a screen showing a specificlocation. The second portable computing device 834 can instruct a userto activate the placed wearable sensor 802 by pressing a button on theplaced wearable sensor 802, for example, by displaying screen 930. Thesecond portable computing device 834 can instruct a user to wait, forexample, by displaying screen 932, while the wearable sensor 802 istested for impedance, such as with impedance tests described herein. Insome cases, impedance is verified, and the memory is updated onimpedance level. If an impedance test fails on a first or a subsequenttry (such as, a second try), a Poor Electrode Contact Alert screen (notshown) may be displayed. If an impedance test fails on yet anothersubsequent try (such as, a third try), a Sensor Failure—No Retry screen(not shown) may be displayed. If impedance is verified (impedance testsucceeds), the process may be repeated if attachments for additionalwearable sensors 802 need replacement. If attachment replacementcompletes for one or more wearable sensors 802, the second portablecomputing device 834 can inform the user that replacement is complete,for example, by displaying screen 934.

Attachments may need to be periodically replaced, as described herein.The second portable computing device 834 can periodically instruct theuser to replace one or more attachments, which can be performed bydisplaying instructions. FIG. 9C is an illustration of a process forguiding a user through replacing one or more attachments. In some cases,through each of the screens, the system displays the next screen inresponse to user input, for example a user may press a button (on ascreen display or a physical button on the second portable computingdevice 834) to go to the next screen showing the next instructions. Instep 941, an application running on a second portable computing device834 alerts a user to replace one or more attachments. The alert can beprovided periodically, such as every 6 hours or less, 12 hours, 18hours, 24 hours, 30 hours, 36 hours, 42 hours, 48 hours, 54 hours, 60hours, 66 hours, or 72 hours, 4 days, 5 days, 6 days, or 7 days or more,or the like or a value therebetween, or a range constructed from any ofthe aforementioned values or values therebetween. In step 943, the userchanges (replaces) one or more attachments (including, for example, allattachments). The application may display several screens on a secondportable computing device 834 to guide a user through replacement of anattachment. In screen 940 (which may be displayed responsive the alertin step 941), the application can request user input as to whether oneor all attachments would be replaced. In some implementations, theoption of replacing more than one but less than all attachments may beprovided. In some cases, in response to user input, a process forinstructing replacement of only one attachment is initiated. In screen942, a diagram of wearable sensor 802 locations can be displayed so thata user can input a selection of which wearable sensor 802 attachmentshould be replaced. Only some wearable sensors 802 may be displayed orallowed to be selected by the user, for example only wearable sensors802 that are currently active and/or in use. A display (not shown) canask a user to confirm the selection of the wearable sensor 802 whoseattachment that is being replaced. The second portable computing device834 can command the selected wearable sensor 802 to enter a sleep state.

In screen 944, a user is instructed to remove the selected wearablesensor 802 from its location on the scalp. In the example of screen 944,the screen of the second portable computing device 834 displays agraphical representation of the wearable sensor 802 location. In screen924, a user is instructed to clean the area where the sticker is placedon the scalp. In screen 926, a user is instructed to place a newattachment (adhesive sticker) onto the wearable sensor 802.Subsequently, additional screens described in connection with FIG. 9Bcan be displayed. The process may be repeated in sequence to replaceattachments for one or more additional wearable sensors 802. Forinstance, the process may repeat screens 942, 944, 924, 926, etc. foreach of the additional wearable sensors 802. As another example, theuser can select multiple wearable sensor 802 attachments for replacementin screen 942, and the process can repeat screens 944, 924, 926, etc.for each of the selected wearable sensors.

FIG. 9D is an illustration of a process for guiding a user throughchanging all attachments. In some cases, by all attachments, it is meantall adhesive attachments for all wearable sensors 802 currently in use.In screen 940, the user can select the option for replacing “allstickers.” In display 950, the user can be instructed to remove each ofthe plurality of wearable sensors 802 from each location on the scalp.In display 952, the user can be instructed to remove all attachmentsfrom each of the plurality of wearable sensors 802. In display 954, theuser can be instructed to clean all areas on the scalp for placement ofeach of the plurality of wearable sensors 802. In display 956, a usercan be instructed to place a new attachment onto each of the pluralityof wearable sensors 802. Subsequently, additional screens similar tothose described in connection with FIG. 9B can be displayed (such asscreens 928, 930, 932, 934).

Provided herein are systems for monitoring of brain activity. Thesystems can include a plurality of wearable sensors 802 configured todetect EEG signals indicative of a brain activity of a user. Eachwearable sensor 802 can include at least two electrodes configured tomonitor the EEG signals when the wearable sensor 802 is positioned on ascalp of the user, and an electronic circuitry configured to process theEEG signals monitored by the at least two electrodes and wirelesslytransmit processed EEG signals to a first portable computing device 832.

The systems can further include a first non-transitory computer readablemedium storing executable instructions that, when executed by at leastone processor of the first portable computing device 832, cause the atleast one processor of the first portable computing device 832 tofacilitate an activation of the plurality of wearable sensors 802 bydisplaying instructions for the on a display of the first portablecomputing device 832. The executable instructions can further cause theat least one processor of the first portable computing device 832 to,subsequent to the activation of the plurality of wearable sensors 802,transfer control of the plurality of wearable sensors 802 to a secondportable computing device 834 to permit the second portable computingdevice 834 configured to be worn by the user to wirelessly receiveprocessed EEG signals. The second portable computing device 834 may notinclude a display or may include a display that is smaller than thedisplay of the first portable computing device 834. The first portablecomputing device 834 can be configured to facilitate activating andpositioning the plurality of wearable sensors 802 on the scalp of theuser and the second portable computing device 834 is configured tofacilitate monitoring of the brain activity of the user and detectingone or more disorders.

The first portable computing device 832 can be a tablet and the secondportable computing device 834 can be a smartwatch. The executableinstructions can further cause the at least one processor to of thefirst portable computing device 832 to, prior to transferring control tothe second portable computing device 834, authenticate the secondportable computing device 834. Authenticating the second portablecomputing device 834 can include scanning a QR code of the secondportable computing device 834.

The systems can further include a second non-transitory computerreadable medium storing executable instructions that, when executed byat least one processor of the second portable computing device 834,cause the at least one processor of the second portable computing device834 to cause display of an alert on the display of the second portablecomputing device 834. The executable instructions can further cause theat least one processor of the second portable computing device 834 tocause display of instructions for resolving the alert on the display ofthe second portable computing device 834. The executable instructionscan further cause the at least one processor of the second portablecomputing device 834 to pause collection of the processed EEG signals.

The executable instructions can cause the at least one processor of thesecond portable computing device 834 to detect and display the alertresponsive to determining that an impedance of at least one wearablesensor of the plurality of wearable sensors does not satisfy animpedance threshold. For example, the signal issue alert 912 of FIG. 9Ais a display of an alert on the display of the second portable computingdevice 834 related to an impedance issue. The instructions can beassociated with replacing an attachment configured to removably attachthe at least one wearable sensor 802 to the scalp of the user. Theinstructions can include causing removal of the at least one wearablesensor 802, replacement of the attachment with another attachment, andrepositioning the at least one wearable sensor 802 on the scalp of theuser. The executable instructions can further cause the at least oneprocessor of the second portable computing device 834 to, responsive toverifying the impedance of the at least one wearable sensor 802 after ithas been repositioned on the scalp of the user, resume collection of theprocessed EEG signals. Verifying the impedance of the at least onewearable sensor 802 can include determining that the impedance of the atleast one wearable sensor 802 satisfies the impedance threshold. Theexecutable instructions can facilitate selection of the at least onewearable sensor 802 from the plurality of wearable sensors 802. The(user) instructions can display a position of the at least one wearablesensor 802 on the scalp of the user.

The executable instructions can cause the at least one processor of thesecond portable computing device 834 to cause display of the alertresponsive to passage of a duration of time since replacement of aplurality of attachments configured to removably attach the plurality ofwearable sensors 802 to the scalp of the user. The duration of time maybe 6 hours or less, 12 hours, 18 hours, 24 hours, 30 hours, 36 hours, 42hours, 48 hours, 54 hours, 60 hours, 66 hours, or 72 hours, 4 days, 5days, 6 days, or 7 days or more, or the like or a value therebetween, ora range constructed from any of the aforementioned values or valuestherebetween.

The systems can further include a second non-transitory computerreadable medium storing executable instructions that, when executed byat least one processor of the second portable computing device 834,cause the at least one processor of the second portable computing device834 to, responsive to a detection of a possible seizure, cause displayof instructions for confirming occurrence of a seizure.

As described herein, the wearable sensors 802 can monitor EEG signalsfor detection of one or more physiological conditions, such as aseizure. EEG data can be processed by one or more recognitiontechniques, such as machine learning techniques, to detect a seizure. Toimprove the detection (such as, to train one or more recognitiontechniques), it may be advantageous to have the user confirm occurrenceoft whether a possible seizure has been detected correctly. FIG. 9Edisplays a process for confirming with a user the occurrence of aseizure. Recording in session screen 916 shows that EEG recording is insession.

In response to user input (such as, a press of a button as described inconnection with FIG. 9A), the second portable computing device 834 candisplay a log event screen 960. The second portable computing device 834can display a screen (such as log event screen 960) instructing a userto indicate whether or not a seizure just occurred. A user may selectyes or no (that a seizure has or has not just occurred) by, for example,pressing a button (as described in connection with FIG. 9A).

If a user inputs that a seizure has occurred, the second portablecomputing device 834 can add a record of an event to the memory. If auser inputs that no seizure has occurred, the second portable computingdevice 834 may not add a record of an event to the memory. If a userinputs that a seizure has occurred, the second portable computing device834 can display a confirm event screen 962. The second portablecomputing device 834 can display a confirm event screen 962automatically after a predetermined amount of time (such as 30 secondsor the like) has elapsed since the log event screen 960 was opened. Theconfirm event screen 962 can indicate to a user that an event indicatingoccurrence of a seizure has been logged. In response to user input orafter the lapse of another predetermined amount of time since displayingconfirm event screen 962, recording in session screen 916 can bedisplayed again.

In some cases, wireless scans (such as Bluetooth scan) are stoppedduring recording sessions. A wireless scan may start again if a wearablesensor 802 disconnects. Real-time data notifications can be enabled forall wearable sensors 802. When EEG recording is in session, the secondportable computing device 834 can receive messages containing real-timedata/events from the plurality of wearable sensors 802 and communicatesmessages containing real-time data/events to a remote server or cloudserver over the Internet. Session end messages can be communicated to aremote server or cloud server. In response to user input, the secondportable computing device 834 can display an options screen (not shown)or a parental lockout screen (not shown).

Synchronizing Independent Wireless EEG Sensors

Each EEG sensor of a plurality of EEG sensors can independently monitorand collect EEG signals without communicating with the other EEGsensors. Collected EEG signals can be wirelessly transmitted to one ormore portable computing device for processing, which can includecollating (or unifying, aligning, or synchronizing) and analyzing EEGsignals to determine occurrence of one or more physiological conditions.At least some of the processing can be performed by a remote computingdevice. It can be advantageous to synchronize one or more of collectionor transmission of EEG signals by the plurality of sensors so thatprocessing is performed correctly.

Provided herein are methods and systems for synchronized monitoring ofbrain activity by a plurality of independent EEG sensors configured todetect EEG signals indicative of a brain activity of a user (such as, apatient). Each sensor can be configured to detect EEG signalsindependent of the other sensors and may not communicate with the othersensors.

Each EEG sensor can include at least two electrodes configured tomonitor the EEG signals when the EEG sensor is positioned on a scalp ofthe user. Each EEG sensor can further include an electronic circuitryconfigured to, based on the signals detected by the at least twoelectrodes process the EEG signals monitored by the at least twoelectrodes and wirelessly transmit the data associated with the brainactivity of the user to one or more portable computing devices.

The system can further includes a non-transitory computer readablemedium storing executable instructions that, when executed by at leastone processor of the one or more portable computing devices, cause theat least one processor to wirelessly transmit a first message to theplurality of EEG sensors to listen to a second message. The executableinstructions can cause the at least one processor to, subsequent totransmitting the first message, wirelessly transmit a second message tothe plurality of EEG sensors, the second message comprising timinginformation. Transmission of the second message can cause the electroniccircuitry of each EEG sensor to set an internal clock to substantiallymatch internal clocks of the other EEG sensors, the internal clock beingused for time stamping recorded signals indicative of the brain activityof the user. Data determined by each EEG wearable sensor can becorrelated with data determined by the EEG wearable sensors to withinapproximately 10 ms or less, 20 ms, 30 ms, 40 ms, 50 ms or more, or thelike, or within a range constructed from any of the aforementionedvalues.

In some cases, no EEG sensor communicates with another EEG sensor. Theexecutable instructions can further cause the at least one processor to,subsequent to wirelessly transmitting the second message, confirm thatthe EEG sensors have set their internal clocks. The executableinstructions can further cause the at least one processor to verify thatthe processed EEG signals received from each EEG sensor are correlatedwith the processed EEG signals determined by the other EEG sensors ofthe plurality of wearable sensors (for example, to within approximately10 ms or less, 20 ms, 30 ms, 40 ms, 50 ms or more, or the like, orwithin a range constructed from any of the aforementioned values). Theexecutable instructions can further cause the at least one processor to,responsive to the verification, transmit the processed EEG signalsreceived from the plurality of EEG sensors to a remote computing device.

The executable instructions can further cause the at least one processorto poll the plurality of EEG sensors for their internal clocks. Theexecutable instructions can further cause the at least one processor to,in response to detecting that a difference between an internal clock ofat least one EEG sensor and an expected internal clock satisfies athreshold, repeat wireless transmission of the first and second messagesto cause the electronic circuitry of the at least one EEG sensor to setthe internal clock. The threshold can be no more than about 10 ms, 20ms, 50 ms, 75 ms, 90 ms, 100 ms, or 200 ms, or within a rangeconstructed from any of the aforementioned values and may be dependenton the specification for the clock synchronization. For instance, athreshold with a higher value would be used for monitoring aphysiological signal that varies less frequently. Monitoring such asignal may be performed even when the internal clocks are lessaccurately synchronized. As another example, a threshold with a lowervalue would be used for monitoring a physiological signal that variesmore frequently. Monitoring such a signal may be necessitate a greateraccuracy of synchronization of the internal clocks.

Provided herein are methods for synchronized monitoring of brainactivity. The methods can include wirelessly transmitting a firstmessage to a plurality of EEG sensors configured to detect EEG signalsindicative of a brain activity of a user (such as, a patient). Each EEGsensor can include at least two electrodes configured to monitor the EEGsignals when the EEG sensor is positioned on a scalp of the user. EachEEG sensor can include an electronic circuitry configured to, based onthe signals detected by the at least two electrodes, determine dataassociated with the brain activity of the user.

The methods can further include, subsequent to transmitting the firstmessage, wirelessly transmitting a second message to the plurality ofEEG sensors. The second message can include timing information.Transmission of the second message can cause the electronic circuitry ofeach EEG sensor to set an internal clock to substantially match internalclocks of the other EEG sensors, for example, within a set of activatedsensors for a sensor session. The internal clock can be used for timestamping recorded signals indicative of the brain activity of the user.

The methods can further include wirelessly receiving the processed EEGsignals from the plurality of EEG sensors and verifying that theprocessed EEG signals received from each EEG sensor are correlated withthe processed EEG signals determined by the other EEG sensors (forexample, to within approximately 10 ms or less, 20 ms, 30 ms, 40 ms, 50ms or more, or the like, or within a range constructed from any of theaforementioned values).

The methods can further include, responsive to the verification,transmitting the processed EEG signals received from the EEG sensors toa remote computing device. The remote computing device can be a portablecomputing device as described herein. In some cases, no EEG sensorcommunicates with another EEG sensor. The methods can include verifyingthat the processed EEG signals received from each EEG sensor iscorrelated with the processed EEG signals determined by the other EEGsensors (for example, to within approximately 10 ms or less, 20 ms, 30ms, 40 ms, 50 ms or more, or the like, or within a range constructedfrom any of the aforementioned values).

The methods can further include confirming that that the plurality ofEEG sensors have set their internal clocks. The methods can furtherinclude polling the plurality of EEG sensors for their internal clocks.The methods can further include in response to detecting that adifference between an internal clock of at least one EEG sensor and anexpected internal clock satisfies a threshold, repeating wirelesstransmission of the first and second messages to cause the electroniccircuitry of the at least one EEG sensor to set the internal clock. Thisway, any unacceptable clock drift can be detected and corrected.

FIG. 10A illustrates a method of synchronizing sensor data for aplurality of independent EEG sensors. The method can be executed by aportable computing device. In step 1010, a first message is sent to eachEEG sensor cause the EEG sensor to listen (or transition to a listeningstate). The first message can be a command sent from the portablecomputing device. The first message can be a directed message sentindividually to each EEG sensor. In some cases, listening is a state ofscanning and waiting for a second command (or second message) thatincludes clock information (such as, a time stamp). The second messagecan be sent, for instance, as an advertising message using the BLEprotocol. BLE mesh capability may be used. The second message can be asingle message broadcast to all EEG sensors (as compared to the firstmessage that is directly sent to each EEG sensor). The reason forsending first and second messages can be that the first message causesthe EEG sensors to enter into the listening state in which the EEGsensors look for a broadcast message that is received by the EEG sensorssimultaneously.

In some cases, a different wireless communication protocol can be used,such as the WiFi protocol, NFC protocol, RFID protocol, or the like. Forprotocols that support direct broadcast to the EEG sensors (such as,WiFi which supports directs broadcast to all devices on a subnet), itwould be sufficient to send a single broadcast message to all EEGdevices. The broadcast message can include clock information, which canbe a time stamp.

In step 1020, the second message can be sent to each EEG sensor tosynchronize the internal clocks of the EEG sensors. The second messagecan be a command to set the clock of the EEG sensor to the portabledevice clock (or some other clock value). Thus, the second message caninclude a clock information (or clock value). As described herein, eachof the plurality of individual sensors can receive the second messagesimultaneously. This way, the internal clocks of EEG sensors will be setto approximately the same clock value (which can be the clock valueincluded in the second message) resulting in synchronous processing ofEEG data received from the EEG sensors since the EEG data cantransmitted by the EEG sensors along with internal clock values, asdescribed herein.

After all EEG sensors receive and process the second message, each EEGsensor can set the internal clock to the same time setting to a desiredtolerance (for example, approximately 10 ms or less, 20 ms, 30 ms, 40ms, 50 ms or more, or the like, or within a range constructed from anyof the aforementioned values). Each individual EEG sensor can record EEGdata with a time stamp derived from the internal clock. EEG data packetsfrom sensors can be sent to a portable computing device independentlyand possibly at different times. The portable computing device maycombine data from the plurality of EEG sensors based on time stamps fromthe individual sensors.

In some cases, if an EEG sensor does not receive the first or secondcommand and does not set its internal clock as described here, when theEEG sensor tries to reconnect with the portable computing device, theportable computing device will recognize that the sensor has notsynchronized its internal clock. The portable computing device may thenrestart the synchronization process of FIG. 10A.

In some implementations, synchronization can be performed as follows.Each EEG sensor can be caused to process an electrical stimulationgenerated by another EEG sensor and sensed by at least two electrodesand record the electrical stimulation along with data associated withthe brain activity of the user. Recording of the electrical stimulationfacilitates combining and processing data associated with the brainactivity of the user collected by the plurality of EEG sensors. As shownin FIG. 10B, in step 1030, an EEG sensor can stimulate the skin byapplying an electrical signal with the electrodes. For example, the EEGsensor can sends a signal (such as railing power through one of theelectrodes), which stimulates the skin to create an electrical tap. Instep 1040, the other EEG sensors can sense the tap through the skin tosynchronize the sensors. Rather than synchronizing the clocks, EEG datacan be synchronized by including in the data information indicating thatthe tap was applied (for the EEG sensor applying the tap) and sensed(for the other EEG sensors). Accordingly, EEG data from different EEGsensors can be combined and aligned by using the information related totap. Synchronization can be initiated by a portable computing devicewhich receives data packets containing tap information.

In some cases, synchronization can be performed as follows. A recordableevent (such as a ping or an instruction to generate stimulation) can beprovided via a portable computing device to one of the EEG sensors. Therecordable event can be relayed by the EEG sensor to the other EEGsensors, and can be recorded by each of the EEG sensors. Data can belater synchronized using the techniques described in connection withFIG. 10B.

ADDITIONAL EXAMPLES

Example 1: A system for monitoring brain activity comprising: aplurality of wearable sensors configured to record a brain activity of auser, each wearable sensor comprising a housing, at least two electrodespositioned on an exterior surface of the housing and configured todetect electroencephalogram (EEG) signals indicative of the brainactivity of the user when the wearable sensor is positioned on a scalpof the user, an electronic circuitry supported by the housing andconfigured to process the EEG signals detected by the at least twoelectrodes, and a power source supported by the housing and configuredto provide power to the electronic circuitry, the housing having anextended, rounded shape; and

a plurality of attachments, each attachment including a first sideshaped to substantially match the extended, rounded shape and configuredto be attached to the exterior surface of the housing of a wearablesensor and a second side configured to removably position the wearablesensor on the scalp of the user, a number of attachments in theplurality of attachments being greater than a number of wearable sensorsin the plurality of wearable sensors.

Example 2: The system of any of the preceding examples, furthercomprising a charger comprising a charger housing configured to receiveand simultaneously charge power sources of at least two wearable sensorsof the plurality of wearable sensors.

Example 3: The system of any of the preceding examples, wherein theextended, rounded shape of the housing is configured to fit around ahairline of the user such that the extended, rounded shape of thehousing facilitates unobtrusive wear of the wearable sensor on the scalpof the user while facilitating collection of the EEG signals.

Example 4: The system of example 3, wherein the housing comprises afirst portion having a first thickness and a second portion having asecond thickness greater than the first thickness.

Example 5: The system of any of the preceding examples, wherein asurface area of the housing is between 16.0 cm² and 10 cm².

Example 6: The system of any of the preceding examples, wherein a volumeof the housing is between 5.0 cm³ and 3.0 cm³.

Example 7: The system of any of the preceding examples, wherein thenumber of attachments in the plurality of attachments comprises thenumber of wearable sensors in the plurality of wearable sensorsmultiplied by a number of days during which the plurality of wearablesensors are configured to record the brain activity of the user.

Example 8: The system of any of the preceding examples, wherein thefirst side of each attachment is configured to be attached to a bottomsurface of the housing.

Example 9: The system of any of the preceding examples, wherein eachattachment of the plurality of attachments comprises hydrocolloidmaterial on the second side of the attachment, the hydrocolloid materialfacilitating repositioning a wearable sensor on the scalp of the user.

Example 10: The system of any of the preceding examples, wherein eachattachment comprises a plurality of layers including one or more of:

a first layer comprising a thermoplastic resin;

a second layer comprising a cured hydrogel;

a third layer comprising an adhesive;

a fourth layer comprising a non-woven fabric;

a fifth layer comprising an adhesive; or

a sixth layer comprising a thermoplastic resin.

Example 11: The system of example 10, wherein the thermoplastic resincomprises PET.

Example 12: The system of any of examples 10 to 11, wherein two or moreof the first, second, third, fourth, fifth, or sixth layers arelaminated to one another such that the cured hydrogel is disposedbetween the first layer and the third layer.

Example 13: The system of any of examples 10 to 12, wherein the thirdand fifth layers form apertures and one or more of the third layer,fourth layer, or the fifth layer includes the cured hydrogel.

Example 14: The system of example 13, wherein the apertures align withthe at least two electrodes of a wearable sensor.

Example 15: A unitary, wireless, and wearable sensor configured formonitoring brain activity comprising:

a housing with an extended, rounded shape configured to fit around ahairline of a user;

at least two electrodes positioned on an exterior surface of the housingand configured to detect electroencephalogram (EEG) signals indicativeof a brain activity of the user when the housing is positioned on ascalp of the user; and

an electronic circuitry supported by the housing and configured toprocess the EEG signals detected by the at least two electrodes andwirelessly communicate processed EEG signal to a remote computingdevice,

wherein the extended, rounded shape of the housing facilitatesunobtrusive wear of the housing on the scalp of the user whilefacilitating collection of the EEG signals.

Example 16: The sensor of example 15, wherein the housing comprises afirst portion having a first thickness and a second portion having asecond thickness greater than the first thickness.

Example 17: The sensor of any of examples 15 to 16, wherein a surfacearea of the housing is between 16.0 cm² and 10 cm².

Example 18: The sensor of any of examples 15 to 17, wherein a volume ofthe housing is between 5.0 cm³ and 3.0 cm³.

Example 19: A kit comprising a plurality of sensors of any of examples15 to 18, wherein each sensor is configured to detectelectroencephalogram (EEG) signals independent of the other sensors.

Example 20: The kit of example 19, further comprising a plurality ofattachments, each attachment including a first side shaped tosubstantially match the extended, rounded shape and configured to beattached to the exterior surface of the housing of a sensor of theplurality of sensors and a second side configured to removably positionthe sensor on the scalp of the user, a number of attachments in theplurality of attachments being greater than a number of sensors in theplurality of sensors.

Example 21: The kit of example 20, wherein the number of attachments inthe plurality of attachments comprises the number of sensors in theplurality of sensors multiplied by a number of days during which theplurality of sensors are configured to record the brain activity of theuser.

Example 22: A system for monitoring brain activity comprising:

a plurality of unitary, wireless, and wearable sensors configured torecord a brain activity of a user, each sensor comprising:

a housing with an extended, rounded shape configured to fit around ahairline of a user;

at least two electrodes positioned on an exterior surface of the housingand configured to detect electroencephalogram (EEG) signals indicativeof a brain activity of the user when the housing is positioned on ascalp of the user; and

an electronic circuitry supported by the housing and configured toprocess the EEG signals detected by the at least two electrodes andwirelessly communicate processed EEG signal to a remote computingdevice,

wherein the extended, rounded shape of the housing facilitatesunobtrusive wear of the housing on the scalp of the user whilefacilitating collection of the EEG signals; and

a plurality of attachments, each attachment including a first sideshaped to substantially match the extended, rounded shape and configuredto be attached to the exterior surface of the housing of a sensor and asecond side configured to removably position the sensor on the scalp ofthe user, a number of attachments in the plurality of attachments beinggreater than a number of sensors in the plurality of sensors.

Example 23: A method for monitoring brain activity comprising:

detaching at least one wearable sensor of a plurality of wearablesensors configured to record a brain activity of a user, each wearablesensor comprising a housing having an extended, rounded shape and atleast two electrodes positioned on an exterior surface of the housingand configured to detect electroencephalogram (EEG) signals indicativeof the brain activity of the user;

replacing a first attachment of a plurality of attachments with a secondattachment of the plurality of attachments, the first and secondattachments including a first side shaped to substantially match theextended, rounded shape and configured to be attached to the exteriorsurface of the housing of the at least one wearable sensor and a secondside configured to removably position the at least one wearable sensoron a scalp of the user, a number of attachments in the plurality ofattachments being greater than a number of wearable sensors in theplurality of wearable sensors;

reattaching the at least one sensor to the scalp of the user by adheringthe second side of the second attachment to the scalp of the user; and

resuming recording of EEG signals indicative of the brain activity ofthe user.

Example 24: A system for monitoring brain activity comprising:

a plurality of wearable sensors configured to detectelectroencephalogram (EEG) signals indicative of a brain activity of auser, each wearable sensor comprising at least two electrodes configuredto monitor the EEG signals when the wearable sensor is positioned on ascalp of the user and an electronic circuitry configured to process theEEG signals monitored by the at least two electrodes; and

a non-transitory computer readable medium storing executableinstructions that, when executed by at least one processor of a portablecomputing device, cause the at least one processor to:

provide instructions to position a wearable sensor of the plurality ofwearable sensors in a location of a plurality of locations on the scalpof the user and activate the wearable sensor;

verify an identification of the wearable sensor;

responsive to verification of the identification of the wearable sensor,verify an impedance of the wearable sensor; and

responsive to verification of the impedance of the wearable sensor,provide instructions to position and activate another wearable sensor ofthe plurality of wearable sensors and perform verification of anidentification and an impedance of the another wearable sensor.

Example 25: The system of example 24, wherein the executable instructionfurther cause the at least one processor to sequentially provideinstructions to position and activate, verify an identification, andverify an impedance of each wearable sensor of the plurality of wearablesensors.

Example 26: The system of example 25, wherein the executable instructionfurther cause the at least one processor to, responsive to verificationof the identification and impedance of each wearable sensor of theplurality of wearable sensors, record the processed EEG signalswirelessly transmitted by the plurality of wearable sensors.

Example 27: The system of any of examples 24 to 26, wherein theexecutable instructions further cause the at least one processor to,responsive to not verifying that the impedance of the wearable sensorsatisfies an impedance threshold, repeat providing instructions,verifying the identification, and verifying the impedance for thewearable sensor.

Example 28: The system of example 27, wherein the executableinstructions further cause the at least one processor to, responsive tonot verifying the impedance of the wearable sensor for a second time,restart providing instructions, verifying the identification, andverifying the impedance for the wearable sensor.

Example 29: The system of any of examples 24 to 28, wherein theexecutable instruction further cause the at least one processor toprovide an alert in response to detecting that at least two wearablesensors of the plurality of wearable sensors have been activated forpositioning in a location of the plurality of locations on the scalp ofthe user.

Example 30: The system of example 29, wherein the executableinstructions further cause the processor to, responsive to detectingthat at least two wearable sensors of the plurality of wearable sensorshave been activated for positioning in a particular location of theplurality of locations on the scalp of the user, restart providinginstructions, verifying the identification, and verifying the impedancefor the plurality of wearable sensors.

Example 31: The system of example 30, wherein detecting that the atleast two wearable sensors have been activated for positioning in theparticular location comprises detecting that multiple sensors have beenactivated substantially simultaneously.

Example 32: The system of any of examples 24 to 31, wherein providinginstructions to position the wearable sensor comprises displayinginstructions on a screen of the portable computing device.

Example 33: The system of example 32, wherein providing instructions toposition the wearable sensor comprises displaying the location on thescreen of the portable computing device and instructions to activate thewearable sensor.

Example 34: The system of any of examples 24 to 33, wherein theexecutable instructions further cause the at least one processor to,prior to providing instructions to position the wearable sensor in thelocation on the scalp of the user, provide instructions to scan or enterthe identification for the wearable sensor.

Example 35: The system of any of examples 24 to 34, wherein providinginstructions to position the wearable sensor in the location on thescalp of the user comprises instructing a use of a plurality ofattachments configured to removably attach the wearable sensor to thescalp of the user.

Example 36: A method for monitoring brain activity comprising:

by at least one processor of a portable computing device:

providing instructions to position a wearable sensor of a plurality ofwearable sensors in a location of a plurality of locations on a scalp ofa user and activate the wearable sensor, the plurality of wearablesensors configured to detect electroencephalogram (EEG) signalsindicative of a brain activity of the user, each wearable sensorcomprising at least two electrodes configured to monitor the EEG signalswhen the wearable sensor is positioned on the scalp of the user and anelectronic circuitry configured to process the EEG signals monitored bythe at least two electrodes;

verifying an identification of the wearable sensor;

responsive to verifying the identification of the wearable sensor,verifying an impedance of the wearable sensor; and

responsive to verifying the impedance of the wearable sensor, providinginstructions to position and activate another wearable sensor of theplurality of wearable sensors and perform verification of anidentification and an impedance of the another wearable sensor.

Example 37: The method of example 36, further comprising sequentiallyproviding instructions to position and activate, verify anidentification, and verify an impedance of each wearable sensor of theplurality of wearable sensors.

Example 38: The method of example 37, further comprising, responsive toverifying the identification and impedance of each wearable sensor ofthe plurality of wearable sensors, recording the processed EEG signalswirelessly transmitted by the plurality of wearable sensors.

Example 39: The method of any of examples 36 to 37, further comprising,responsive to not verifying that the impedance of the wearable sensorsatisfies an impedance threshold, repeating providing instructions,verifying the identification, and verifying the impedance for thewearable sensor.

Example 40: The method of example 39, further comprising, responsive tonot verifying the impedance of the wearable sensor for a second time,restarting providing instructions, verifying the identification, andverifying the impedance for the wearable sensor.

Example 41: The method of any of examples 36 to 40, further comprisingproviding an alert in response to detecting that at least two wearablesensors of the plurality of wearable sensors have been activated forpositioning in a location of the plurality of locations on the scalp ofthe user.

Example 42: The method of example 41, further comprising, responsive todetecting that at least two wearable sensors of the plurality ofwearable sensors have been activated for positioning in a particularlocation of the plurality of locations on the scalp of the user,restarting providing instructions, verifying the identification, andverifying the impedance for the plurality of wearable sensors.

Example 43: The method of example 42, wherein detecting that the atleast two wearable sensors have been activated for positioning in theparticular location comprises detecting that multiple sensors have beenactivated substantially simultaneously.

Example 44: The method of any of examples 36 to 43, wherein providinginstructions to position the wearable sensor comprises displayinginstructions on a screen of the portable computing device.

Example 45: The method of example 44, wherein providing instructions toposition the wearable sensor comprises displaying the location on thescreen of the portable computing device and instructions to activate thewearable sensor.

Example 46: The method of any of examples 36 to 45, further comprising,prior to providing instructions to position the wearable sensor in thelocation on the scalp of the user, providing instructions to scan orenter the identification for the wearable sensor.

Example 47: The method of any of examples 36 to 46, wherein providinginstructions to position the wearable sensor in the location on thescalp of the user comprises instructing a use of a plurality ofattachments configured to removably attach the wearable sensor to thescalp of the user.

Example 48: A method for monitoring of brain activity comprising:activating a plurality of wearable sensors configured to detectelectroencephalogram (EEG) signals indicative of a brain activity of auser and positioned in a plurality of locations on a scalp of the user,each wearable sensor comprising at least two electrodes configured tomonitor the EEG signals when the wearable sensor is positioned on thescalp of the user and an electronic circuitry configured to process theEEG signals monitored by the at least two electrodes and wirelesslytransmit processed EEG signals to a first portable computing device, theactivating comprising following instructions displayed on a display ofthe first portable computing device; and

subsequent to the activation of the plurality of wearable sensors,transferring control of the plurality of wearable sensors to a secondportable computing device configured to be worn by the user to permitthe second portable computing device to wirelessly receive the processedEEG signals, the second portable computing device not including adisplay or including a display that is smaller than the display of thefirst portable computing device,

wherein the first portable computing device is configured to facilitateactivating and positioning the plurality of wearable sensors on thescalp of the user and the second portable computing device is configuredto facilitate monitoring of the brain activity of the user and detectingone or more disorders.

Example 49: The method of example 48, wherein transferring controlcauses the first portable computing device to cease wirelessly receivingthe processed EEG signals.

Example 50: The method of any of examples 48 to 49, wherein the firstportable computing device comprises a tablet and the second portablecomputing device comprises a smartwatch.

Example 51: The method of any of examples 48 to 50, further comprising,prior to transferring control to the second portable computing device,authenticating the second portable computing device.

Example 52: The method of example 51, wherein authenticating the secondportable computing device comprises scanning a QR code of the secondportable computing device.

Example 53: The method of any of examples 48 to 52, further comprising,responsive to an alert displayed on the display of the second portablecomputing device, causing the second portable computing device todisplay instructions for resolving the alert and following theinstructions to resolve the alert.

Example 54: The method of example 53, wherein the instructions areassociated with replacing an attachment configured to removably attach awearable sensor of the plurality of wearable sensors to the scalp of theuser, and wherein the method further comprises, responsive to theinstructions, removing the wearable sensor, replacing the attachmentwith another attachment, and repositioning the wearable sensor on thescalp of the user.

Example 55: The method of any of examples 53 to 54, wherein theinstructions are associated with replacing a plurality of attachmentsconfigured to removably attach the plurality of wearable sensors to thescalp of the user, and wherein the method further comprises, responsiveto the instructions, removing the plurality of wearable sensors,replacing the plurality of attachments with another plurality ofattachments, and repositioning the plurality of wearable sensors on thescalp of the user.

Example 56: A system for monitoring of brain activity comprising:

a plurality of wearable sensors configured to detectelectroencephalogram (EEG) signals indicative of a brain activity of auser, each wearable sensor comprising at least two electrodes configuredto monitor the EEG signals when the wearable sensor is positioned on ascalp of the user and an electronic circuitry configured to process theEEG signals monitored by the at least two electrodes and wirelesslytransmit processed EEG signals to a first portable computing device;

a first non-transitory computer readable medium storing executableinstructions that, when executed by at least one processor of the firstportable computing device, cause the at least one processor of the firstportable computing device to:

facilitate an activation of the plurality of wearable sensors bydisplaying instructions on a display of the first portable computingdevice; and

subsequent to the activation of the plurality of wearable sensors,transfer control of the plurality of wearable sensors to a secondportable computing device to permit the second portable computing deviceconfigured to be worn by the user to wirelessly receive processed EEGsignals, the second portable computing device not including a display orincluding a display that is smaller than the display of the firstportable computing device,

wherein the first portable computing device is configured to facilitateactivating and positioning the plurality of wearable sensors on thescalp of the user and the second portable computing device is configuredto facilitate monitoring of the brain activity of the user and detectingone or more disorders.

Example 57: The system of example 56, wherein the first portablecomputing device comprises a tablet and the second portable computingdevice comprises a smartwatch.

Example 58: The system of any of examples 56 to 57, wherein theexecutable instructions further cause the at least one processor to ofthe first portable computing device to, prior to transferring control tothe second portable computing device, authenticate the second portablecomputing device.

Example 59: The system of example 58, wherein authenticating the secondportable computing device comprises scanning a QR code of the secondportable computing device.

Example 60: The system of any of examples 56 to 59 further comprising asecond non-transitory computer readable medium storing executableinstructions that, when executed by at least one processor of the secondportable computing device, cause the at least one processor of thesecond portable computing device to:

cause display of an alert on the display of the second portablecomputing device;

cause display of user instructions for resolving the alert on thedisplay of the second portable computing device; and

pause collection of the processed EEG signals.

Example 61: The system of example 60, wherein the executableinstructions cause the at least one processor of the second portablecomputing device to detect the alert responsive to determining that animpedance of at least one wearable sensor of the plurality of wearablesensors does not satisfy an impedance threshold.

Example 62: The system of example 61, wherein:

the user instructions are associated with replacing an attachmentconfigured to removably attach the at least one wearable sensor to thescalp of the user, the instructions comprising causing removal of the atleast one wearable sensor, replacement of the attachment with anotherattachment, and repositioning the at least one wearable sensor on thescalp of the user; and

the executable instructions further cause the at least one processor ofthe second portable computing device to, responsive to verifying theimpedance of the at least one wearable sensor after it has beenrepositioned on the scalp of the user, resume collection of theprocessed EEG signals.

Example 63: The system of example 62, wherein verifying the impedance ofthe at least one wearable sensor comprises determining that theimpedance of the at least one wearable sensor satisfies the impedancethreshold.

Example 64: The system of any of examples 62 to 63, wherein theexecutable instructions facilitate selection of the at least onewearable sensor from the plurality of wearable sensors, and wherein theinstructions display a position of the at least one wearable sensor onthe scalp of the user.

Example 65: The system of any of examples 60 to 64, wherein theexecutable instructions cause the at least one processor of the secondportable computing device to cause display of the alert responsive topassage of a duration of time since replacement of a plurality ofattachments configured to removably attach the plurality of wearablesensors to the scalp of the user.

Example 66: The system of example 65, wherein the duration of timecomprises 24 hours.

Example 67: The system of any of examples 56 to 66 further comprising asecond non-transitory computer readable medium storing executableinstructions that, when executed by at least one processor of the secondportable computing device, cause the at least one processor of thesecond portable computing device to:

responsive to a detection of a possible seizure, cause display ofinstructions for confirming occurrence of a seizure.

Example 68: A system for synchronized monitoring of brain activitycomprising:

a plurality of wearable sensors configured to detectelectroencephalogram (EEG) signals indicative of a brain activity of auser, each wearable sensor comprising at least two electrodes configuredto configured to monitor the EEG signals when the wearable sensor ispositioned on a scalp of the user and an electronic circuitry configuredto process the EEG signals monitored by the at least two electrodes andwirelessly transmit processed EEG signals to a portable computingdevice; and

a non-transitory computer readable medium storing executableinstructions that, when executed by at least one processor of theportable computing device, cause the at least one processor to:

wirelessly transmit a message including a clock information to theplurality of wearable sensors; and

cause the electronic circuitry of each wearable sensor of the pluralityof wearable sensors to set an internal clock to the clock information sothat the internal clock substantially matches internal clocks of theother wearable sensors of the plurality of wearable sensors, theinternal clock being used for time stamping recorded signals indicativeof the brain activity of the user, wherein data determined by eachwearable sensor of the plurality of wearable sensors is correlated withdata determined by the other wearable sensors of the plurality ofwearable sensors to no more than 200 ms.

Example 69: The system of example 68, wherein no wearable sensor of theplurality of wearable sensors communicates with another wearable sensorof the plurality of wearable sensors.

Example 70: The system of any of examples 68 to 69, wherein datadetermined by each wearable sensor of the plurality of wearable sensorsis correlated with data determined by the other wearable sensors of theplurality of wearable sensors to no more than 50 ms.

Example 71: The system of any of examples 66 to 68, wherein theexecutable instructions further cause the at least one processor to,subsequent to wirelessly transmitting the message, confirm that theplurality of wearable sensors have set their internal clocks.

Example 72: The system of any of examples 68 to 71, wherein theexecutable instructions further cause the at least one processor toverify that the processed EEG signals received from each wearable sensorof the plurality of wearable sensors are correlated with the processedEEG signals determined by the other wearable sensors of the plurality ofwearable sensors to no more than 200 ms.

Example 73: The system of example 72, wherein the executableinstructions further cause the at least one processor to, responsive tothe verifying, transmit the processed EEG signals received from theplurality of wearable sensors to a remote computing device.

Example 74: The system of any of examples 68 to 73, wherein theexecutable instructions further cause the at least one processor to:

poll the plurality of wearable sensors for their internal clocks; and

in response to detecting that a difference between an internal clock ofat least one wearable sensor of the plurality of wearable sensors and anexpected internal clock satisfies a threshold, repeat wirelesstransmission of the message to cause the electronic circuitry of the atleast one wearable sensor to set the internal clock.

Example 75: The system of any of examples 68 to 74, wherein theexecutable instructions cause the at least one processor to wirelesslytransmitting the message by:

wirelessly transmitting a first message to each wearable sensor of theplurality of wearable sensors and cause the electronic circuitry of theplurality of wearable sensors to listen to a second message; and

subsequent to transmitting the first message, wirelessly broadcasting asecond message to the plurality of wearable sensors, the second messagecomprising the clock information.

Example 76: The system of example 75, wherein the first and secondmessages are transmitted using Bluetooth low energy (BLE) protocol.

Example 77: A method for synchronized monitoring of brain activitycomprising:

wirelessly transmitting a message including a clock information to aplurality of wearable sensors, the plurality of wearable sensorsconfigured to detect electroencephalogram (EEG) signals indicative of abrain activity of a user, each wearable sensor comprising at least twoelectrodes configured to configured to monitor the EEG signals when thewearable sensor is positioned on a scalp of the user and an electroniccircuitry configured to process the EEG signals monitored by the atleast two electrodes and wirelessly transmit processed EEG signals to aportable computing device;

cause the electronic circuitry of each wearable sensor of the pluralityof wearable sensors to set an internal clock to the clock information sothat the internal clock substantially matches internal clocks of theother wearable sensors of the plurality of wearable sensors, theinternal clock being used for time stamping recorded signals indicativeof the brain activity of the user;

wirelessly receiving the processed EEG signals from the plurality ofwearable sensors and verifying that the processed EEG signals receivedfrom each wearable sensor of the plurality of wearable sensors arecorrelated with the processed EEG signals determined by the otherwearable sensors of the plurality of wearable sensors to no more than200 ms; and

responsive to the verifying, transmitting the processed EEG signalsreceived from the plurality of wearable sensors to a remote computingdevice.

Example 78: The method of example 77, wherein no wearable sensor of theplurality of wearable sensors communicates with another wearable sensorof the plurality of wearable sensors.

Example 79: The method of any of examples 77 to 78, wherein verifyingcomprises verifying that the processed EEG signals received from eachwearable sensor of the plurality of wearable sensors are correlated withthe processed EEG signals determined by the other wearable sensors ofthe plurality of wearable sensors to no more than 50 ms.

Example 80: The method of any of examples 77 to 79, further comprisingconfirming that that the plurality of wearable sensors have set theirinternal clocks.

Example 81: The method of example 80, further comprising:

polling the plurality of wearable sensors for their internal clocks; and

in response to detecting that a difference between an internal clock ofat least one wearable sensor of the plurality of wearable sensors and anexpected internal clock satisfies a threshold, repeating wirelesstransmission of the message to cause the electronic circuitry of the atleast one wearable sensor to set the internal clock.

Example 82: The method of any of examples 77 to 81, wherein wirelesslytransmitting the message comprises:

wirelessly transmitting a first message to each wearable sensor of theplurality of wearable sensors and cause the electronic circuitry of theplurality of wearable sensors to listen to a second message; and

subsequent to transmitting the first message, wirelessly broadcasting asecond message to the plurality of wearable sensors, the second messagecomprising the clock information.

Example 83: The method of example 82, wherein the first and secondmessages are transmitted using Bluetooth low energy (BLE) protocol.

Example 84: A system for synchronized monitoring of brain activitycomprising:

a plurality of wearable sensors configured to record a brain activity ofa user, each wearable sensor comprising at least two electrodesconfigured to detect signals indicative of the brain activity of theuser when the wearable sensor is positioned on a scalp of the user andan electronic circuitry configured to, based on the signals detected bythe at least two electrodes, determine data associated with the brainactivity of the user; and

a non-transitory computer readable medium storing instructions that,when executed by at least one processor of the electronic circuitry of awearable sensor of a plurality of wearable sensors, cause the at leastone processor to:

cause at least one two electrodes of the wearable sensor to apply anelectrical stimulation configured to be sensed by other wearable sensorsof the plurality of wearable sensors; and

cause an electronic circuitry of each wearable sensor of the otherwearable sensors to process the electrical stimulation sensed by atleast two electrodes and record the electrical stimulation along withdata associated with the brain activity of the user, wherein recordingof the electrical stimulation facilitates combining and processing dataassociated with the brain activity of the user collected by theplurality of wearable sensors.

One or more features of any one of the foregoing examples can be usedwith one or more features of any other example.

Other Variations

The general principles described herein may be extended to otherscenarios. For example, for intensive care in pediatric and adults twosensors, four sensors, eight sensors, or various combination of sensorsmay be used.

Various other configurations are may also be used, with particularelements that are depicted as being implemented in hardware may insteadbe implemented in software, firmware, or a combination thereof. One ofordinary skill in the art will recognize various alternatives to thespecific embodiments described herein.

The specification and figures describe particular embodiments which areprovided for ease of description and illustration and are not intendedto be restrictive. Embodiments may be implemented to be used in variousenvironments without departing from the spirit and scope of thedisclosure.

At least some elements of a device of the present application can becontrolled and at least some steps of a method of the invention can beeffectuated, in operation with a programmable processor governed byinstructions stored in a memory. The memory may be random access memory(RAM), read-only memory (ROM), flash memory or any other memory, orcombination thereof, suitable for storing control software or otherinstructions and data. Those skilled in the art should also readilyappreciate that instructions or programs defining the functions of thepresent invention may be delivered to a processor in many forms,including, but not limited to, information permanently stored onnon-writable storage media (for example read-only memory devices withina computer, such as ROM, or devices readable by a computer I/Oattachment, such as CD-ROM or DVD disks), information alterably storedon writable storage media (for example floppy disks, removable flashmemory and hard drives) or information conveyed to a computer throughcommunication media, including wired or wireless computer networks. Inaddition, while the invention may be embodied in software, the functionsnecessary to implement the invention may optionally or alternatively beembodied in part or in whole using firmware and/or hardware components,such as combinatorial logic, Application Specific Integrated Circuits(ASICs), Field-Programmable Gate Arrays (FPGAs) or other hardware orsome combination of hardware, software and/or firmware components.

In various embodiments, input from a user may be requested. Examples ofmethods for receiving user input, such as receiving a button press froma user, are illustrative and not by means of limitation. Alternativemethods of receiving user input may be used, including receiving abutton press on a touch screen, a physical button press on a device, aswipe, a tap, any other touch gestures, a spoken (audio) input, etc.

Various modifications to the implementations described in thisdisclosure may be readily apparent to those skilled in the art, and thegeneric principles defined herein may be applied to otherimplementations without departing from the spirit or scope of thisdisclosure. Thus, the claims are not intended to be limited to theimplementations shown herein, but are to be accorded the widest scopeconsistent with this disclosure, the principles and the novel featuresdisclosed herein.

Certain features that are described in this specification in the contextof separate implementations also can be implemented in combination in asingle implementation. Conversely, various features that are describedin the context of a single implementation also can be implemented inmultiple implementations separately or in any suitable subcombination.Moreover, although features may be described above as acting in certaincombinations and even initially claimed as such, one or more featuresfrom a claimed combination can in some cases be excised from thecombination, and the claimed combination may be directed to asubcombination or variation of a subcombination.

Depending on the embodiment, certain acts, events, or functions of anyof the processes or algorithms described herein can be performed in adifferent sequence, can be added, merged, or left out altogether.Moreover, in certain embodiments, operations or events can be performedconcurrently, for example, through multi-threaded processing, interruptprocessing, or multiple processors or processor cores or on otherparallel architectures, rather than sequentially.

The various illustrative logical blocks, modules, routines, andalgorithm steps described in connection with the embodiments disclosedherein can be implemented as electronic hardware, or as a combination ofelectronic hardware and executable software. To clearly illustrate thisinterchangeability, various illustrative components, blocks, modules,and steps have been described above generally in terms of theirfunctionality. Whether such functionality is implemented as hardware, oras software that runs on hardware, depends upon the particularapplication and design constraints imposed on the overall system. Thedescribed functionality can be implemented in varying ways for eachparticular application, but such implementation decisions should not beinterpreted as causing a departure from the scope of the disclosure.

Moreover, the various illustrative logical blocks and modules describedin connection with the embodiments disclosed herein can be implementedor performed by a machine, such as a machine learning service server, adigital signal processor (DSP), an application specific integratedcircuit (ASIC), a field programmable gate array (FPGA) or otherprogrammable logic device, discrete gate or transistor logic, discretehardware components, or any combination thereof designed to perform thefunctions described herein. A machine learning service server can be orinclude a microprocessor, but in the alternative, the machine learningservice server can be or include a controller, microcontroller, or statemachine, combinations of the same, or the like configured to generateand publish machine learning services backed by a machine learningmodel. A machine learning service server can include electricalcircuitry configured to process computer-executable instructions.Although described herein primarily with respect to digital technology,a machine learning service server may also include primarily analogcomponents. For example, some or all of the modeling, simulation, orservice algorithms described herein may be implemented in analogcircuitry or mixed analog and digital circuitry. A computing environmentcan include any type of computer system, including, but not limited to,a computer system based on a microprocessor, a mainframe computer, adigital signal processor, a portable computing device, a devicecontroller, or a computational engine within an appliance, to name afew.

The elements of a method, process, routine, or algorithm described inconnection with the embodiments disclosed herein can be embodieddirectly in hardware, in a software module executed by a machinelearning service server, or in a combination of the two. A softwaremodule can reside in RAM memory, flash memory, ROM memory, EPROM memory,EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or anyother form of a non-transitory computer-readable storage medium. Anillustrative storage medium can be coupled to the machine learningservice server such that the machine learning service server can readinformation from, and write information to, the storage medium. In thealternative, the storage medium can be integral to the machine learningservice server. The machine learning service server and the storagemedium can reside in an ASIC. The ASIC can reside in a user terminal. Inthe alternative, the machine learning service server and the storagemedium can reside as discrete components in a user terminal (forexample, access device or network service client device).

Conditional language used herein, such as, among others, “can,” “could,”“might,” “may,” “for example,” and the like, unless specifically statedotherwise, or otherwise understood within the context as used, isgenerally intended to convey that certain embodiments include, whileother embodiments do not include, certain features, elements and/orsteps. Thus, such conditional language is not generally intended toimply that features, elements and/or steps are in any way required forone or more embodiments or that one or more embodiments necessarilyinclude logic for deciding, with or without other input or prompting,whether these features, elements and/or steps are included or are to beperformed in any particular embodiment. The terms “comprising,”“including,” “having,” and the like are synonymous and are usedinclusively, in an open-ended fashion, and do not exclude additionalelements, features, acts, operations, and so forth. Also, the term “or”is used in its inclusive sense (and not in its exclusive sense) so thatwhen used, for example, to connect a list of elements, the term “or”means one, some, or all of the elements in the list.

Disjunctive language such as the phrase “at least one of X, Y, or Z,”unless specifically stated otherwise, is otherwise understood with thecontext as used in general to present that an item, term, etc., may beeither X, Y, or Z, or any combination thereof (for example, X, Y, and/orZ). Thus, such disjunctive language is not generally intended to, andshould not, imply that certain embodiments require at least one of X, atleast one of Y, or at least one of Z to each be present.

Unless otherwise explicitly stated, articles such as “a” or “an” shouldgenerally be interpreted to include one or more described items.Accordingly, phrases such as “a device configured to” are intended toinclude one or more recited devices. Such one or more recited devicescan also be collectively configured to carry out the stated recitations.For example, “a processor configured to carry out recitations A, B andC” can include a first processor configured to carry out recitation Aworking in conjunction with a second processor configured to carry outrecitations B and C.

While the above detailed description has shown, described, and pointedout novel features as applied to various embodiments, it can beunderstood that various omissions, substitutions, and changes in theform and details of the devices or algorithms illustrated can be madewithout departing from the spirit of the disclosure. As can berecognized, certain embodiments described herein can be embodied withina form that does not provide all of the features and benefits set forthherein, as some features can be used or practiced separately fromothers. The scope of certain embodiments disclosed herein is indicatedby the appended claims rather than by the foregoing description. Allchanges which come within the meaning and range of equivalency of theclaims are to be embraced within their scope.

What is claimed is:
 1. A system for monitoring brain activitycomprising: a plurality of wearable sensors configured to record a brainactivity of a user, each wearable sensor comprising a housing, at leasttwo electrodes positioned on an exterior surface of the housing andconfigured to detect electroencephalogram (EEG) signals indicative ofthe brain activity of the user when the wearable sensor is positioned ona scalp of the user, an electronic circuitry supported by the housingand configured to process the EEG signals detected by the at least twoelectrodes, and a power source supported by the housing and configuredto provide power to the electronic circuitry, the housing having anelongated, rounded shape with a concave first side and a convex secondside positioned opposite the concave first side, the concave first sideand the convex second side configured to protrude from the scalp of theuser when the housing is positioned on the scalp of the user, andthickness of the housing increasing from the concave first side to theconvex second side; and a plurality of attachments, each attachmentincluding a first side shaped to substantially match the elongated,rounded shape of a housing of a wearable sensor of the plurality ofwearable sensors and configured to be attached to the exterior surfaceof the housing and a second side configured to removably position thewearable sensor of the plurality of wearable sensors on the scalp of theuser, a number of attachments in the plurality of attachments beinggreater than a number of wearable sensors in the plurality of wearablesensors.
 2. The system of claim 1, further comprising a chargerincluding a charger housing configured to receive and simultaneouslycharge power sources of at least two wearable sensors of the pluralityof wearable sensors.
 3. The system of claim 1, wherein the elongated,rounded shape of a housing of a wearable sensor of the plurality ofwearable sensors is configured to fit around a hairline of the user suchthat the elongated, rounded shape of the housing facilitates unobtrusivewear of the wearable sensor on the scalp of the user while facilitatingcollection of the EEG signals.
 4. The system of claim 1, wherein asurface area of a housing of a wearable sensor of the plurality ofwearable sensors is between 16.0 cm² and 10 cm².
 5. The system of claim1, wherein a volume of a housing of a wearable sensor of the pluralityof wearable sensors is between 5.0 cm³ and 3.0 cm³.
 6. The system ofclaim 1, wherein the number of attachments in the plurality ofattachments comprises the number of wearable sensors in the plurality ofwearable sensors multiplied by a number of days during which theplurality of wearable sensors are configured to record the brainactivity of the user.
 7. The system of claim 1, wherein a first side ofeach attachment is configured to be attached to a bottom surface of ahousing of a wearable sensor of the plurality of wearable sensors. 8.The system of claim 1, wherein each attachment of the plurality ofattachments comprises hydrocolloid material on a second side of theattachment, the hydrocolloid material facilitating repositioning awearable sensor of the plurality of wearable sensors on the scalp of theuser.
 9. The system of claim 1, wherein each attachment comprises aplurality of layers including: a first layer comprising a thermoplasticresin; a second layer comprising a cured hydrogel; a third layercomprising an adhesive; a fourth layer comprising a non-woven fabric; afifth layer comprising an adhesive; and a sixth layer comprising athermoplastic resin.
 10. The system of claim 9, wherein thethermoplastic resin comprises polyethylene terephthalate (PET).
 11. Thesystem of claim 9, wherein the first and third layers are laminated toone another such that the second layer comprising the cured hydrogel isdisposed between the first layer and the third layer.
 12. The system ofclaim 9, wherein the third and fifth layers form apertures and one ormore of the third layer, fourth layer, or the fifth layer includes thecured hydrogel.
 13. The system of claim 12, wherein the apertures alignwith the at least two electrodes of a wearable sensor of the pluralityof wearable sensors.
 14. A unitary, wireless, and wearable sensorconfigured for monitoring brain activity comprising: a housing with anelongated, rounded shape configured to fit around a hairline of a user,the housing comprising a concave first side and a convex second sidepositioned opposite the concave first side, the concave first side andthe convex second side configured to protrude from a scalp of the userwhen the housing is positioned on the scalp of the user, and thicknessof the housing increasing from the concave first side to the convexsecond side; at least two electrodes positioned on an exterior surfaceof the housing and configured to detect electroencephalogram (EEG)signals indicative of a brain activity of the user when the housing ispositioned on the scalp of the user; and an electronic circuitrysupported by the housing and configured to process the EEG signalsdetected by the at least two electrodes and wirelessly communicateprocessed EEG signal to a remote computing device, wherein theelongated, rounded shape of the housing facilitates unobtrusive wear ofthe housing on the scalp of the user while facilitating collection ofthe EEG signals.
 15. The sensor of claim 14, wherein a surface area ofthe housing is between 16.0 cm² and 10 cm².
 16. The sensor of claim 14,wherein a volume of the housing is between 5.0 cm³ and 3.0 cm³.
 17. Akit comprising a plurality of sensors of claim 14, wherein each sensoris configured to detect electroencephalogram (EEG) signals independentof the other sensors.
 18. The kit of claim 17, further comprising aplurality of attachments, each attachment including a first side shapedto substantially match the elongated, rounded shape of a housing of asensor of the plurality of sensors and configured to be attached to theexterior surface of the housing and a second side configured toremovably position the sensor on the scalp of the user, a number ofattachments in the plurality of attachments being greater than a numberof sensors in the plurality of sensors.
 19. The kit of claim 18, whereinthe number of attachments in the plurality of attachments comprises thenumber of sensors in the plurality of sensors multiplied by a number ofdays during which the plurality of sensors are configured to record thebrain activity of the user.
 20. A system for monitoring brain activitycomprising: a plurality of unitary, wireless, and wearable sensorsconfigured to record a brain activity of a user, each sensor comprising:a housing with an elongated, rounded shape configured to fit around ahairline of a user, the housing comprising a concave first side and aconvex second side positioned opposite the concave first side, theconcave first side and the convex second side configured to protrudefrom a scalp of the user when the housing is positioned on the scalp ofthe user, and thickness of the housing increasing from the concave firstside to the convex second side; at least two electrodes positioned on anexterior surface of the housing and configured to detectelectroencephalogram (EEG) signals indicative of a brain activity of theuser when the housing is positioned on the scalp of the user; and anelectronic circuitry supported by the housing and configured to processthe EEG signals detected by the at least two electrodes and wirelesslycommunicate processed EEG signal to a remote computing device, whereinthe elongated, rounded shape of the housing facilitates unobtrusive wearof the housing on the scalp of the user while facilitating collection ofthe EEG signals; and a plurality of attachments, each attachmentincluding a first side shaped to substantially match the elongated,rounded shape of a housing of a sensor of the plurality of unitary,wireless, and wearable sensors and configured to be attached to theexterior surface of the housing and a second side configured toremovably position the sensor on the scalp of the user, a number ofattachments in the plurality of attachments being greater than a numberof sensors in the plurality of unitary, wireless, and wearable sensors.21. The system of claim 20, wherein the number of attachments in theplurality of attachments comprises the number of sensors in theplurality of unitary, wireless, and wearable sensors multiplied by anumber of days during which the plurality of unitary, wireless, andwearable sensors are configured to record the brain activity of theuser.
 22. The system of claim 20, wherein a surface area of a housing ofa sensor of the plurality of unitary, wireless, and wearable sensors isbetween 16.0 cm² and 10 cm², and wherein a volume of the housing isbetween 5.0 cm³ and 3.0 cm³.